Publications

Text Books

  1. Liang Lin, Dongyu Zhang, Ping Luo, and Wangmeng Zuo, “Human Centric Visual Analysis with Deep Learning”, Springer, 2019. [PDF]

  2. Ziliang Chen, and Liang Lin, “Multi-Source Domain Adaptation by Deep CockTail Networks”, Chapter in Domain Adaptation in Computer Vision with Deep Learning, Springer, 2020. [PDF]

  3. Qingxing Cao, Wentao Wan, Xiaodan Liang, and Liang Lin, “Graph Reasoning Network and Application”, Chapter in Neuro-Symbolic Artificial Intelligence: The State of the Art, Springer, 2021.

Selected Journal Papers    (* indicates I am the paper’s corresponding author)

  1. Yang Liu, Guanbin Li, and Liang Lin*, “Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023. [PDF]

  2. Bingqian Lin, Yanxin Long, Yi Zhu, Fengda Zhu, Xiaodan Liang, Qixiang Ye, and Liang Lin, “Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), DOI: 10.1109/TPAMI.2023.3273594, 2023. [PDF]

  3. Yinya Huang, Lemao Liu, Kun Xu, Meng Fang, Liang Lin, and Xiaodan Liang, Discourse-Aware Graph Networks for Textual Logical Reasoning, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023. [PDF]

  4. Xipeng Chen, Junzheng Zhang, Keze Wang, Pengxu Wei, and Liang Lin*, “Multi-Person 3D Pose Esitmation with Occlusion Reasoning”, IEEE Transactions on Multimedia (T-MM), DOI: 10.1109/TMM.2023.3272736, 2023. [PDF]

  5. Ziyi Tang, Ruimao Zhang, Zhanglin Peng, Jinrui Chen, and Liang Lin, “Multi-Stage Spatio-Temporal Aggregation Transformer for Video Person Re-identification”, IEEE Transactions on Multimedia (T-MM), DOI: 10.1109/TMM.2022.3231103, 2023. [PDF]

  6. Pengxu Wei, Ziwei Xie, Guanbin Li, and Liang Lin*, “Taylor Neural Network for Real-World Image Super-Resolution”, IEEE Transactions on Image Processing (T-IP), 32(3): 1942-1951, 2023. [PDF]

  7. Junying Huang, Junhao Cao, Liang Lin, and Dongyu Zhang, “IRA-FSOD: Instant-Response and Accurate Few-shot Object Detector”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT),  DOI: 10.1109/TCSVT.2023.3272612, 2023. [PDF]

  8. Changxin Huang, Guangrun Wang, Zhibo Zhou, Ronghui Zhang, and Liang Lin*, “Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), DOI: 10.1109/TPAMI.2022.3223407, 2022. [PDF]

  9. Hao Li, Jinghui Qin, Yukai Shi, Zhijing Yang, Pengxu Wei, Jinshan Pan, and Liang Lin, “Real-World Image Super-Resolution by Exclusionary Dual-Learning”, IEEE Transactions on Multimedia (T-MM), DOI: 10.1109/TMM.2022.3181457, 2022. [PDF]

  10. Jinghui Qin, Zhicheng Yang, Jiaqi Chen, Xiaodan Liang, and Liang Lin, “Template-Based Contrastive Distillation Pretraining for Math Word Problem Solving”, IEEE Transactions on Neural Network and Learning Systems (T-NNLS), DOI: 10.1109/TNNLS.2023.3265173, 2023. [PDF]

  11. Si Liu, Renda Bao, Defa Zhu, Shaofei Huang, Qiong Yan, Liang Lin, and Chao Dong, “Fine-grained Face Editing via Personalized Spatial-aware Affine Modulation”, IEEE Transactions on Multimedia (T-MM), DOI: 10.1109/TMM.2022.3172548, 2023 [PDF]

  12. Shuai Lin, Chen Liu, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric Xing, and Xiaodan Liang, “Prototypical Graph Contrastive Learning”, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3191086, 2023. [PDF]

  13. Zhijing Yang, Junyang Chen, Yukai Shi, Hao Li, Tianshui Chen, and Liang Lin, “OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup”, IEEE Transactions on Multimedia (T-MM), 2023. [PDF] [Code]

  14. Lingbo Liu, Zewei Yang, Guanbin Li, Kuo Wang, Tianshui Chen, and Liang Lin*, “Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), DOI: 10.1109/TNNLS.2022.3141821, 2022. [PDF] [Code]

  15. Yuying Zhu, Yang Zhang, Lingbo Liu, Yang Liu, Guanbin Li, Mingzhi Mao, and Liang Lin, “Hybrid-Order Representation Learning for Electricity Theft Detection”, IEEE Transactions on Industrial Informatics (T-II), 2022. [PDF]

  16. Lingbo Liu, Yuying Zhu, Guanbin Li, Ziyi Wu, Lei Bai, and Liang Lin*, “Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 45(3): 3574-3589, 2023. [PDF] [Code]

  17. Tianshui Chen, Tao Pu, Hefeng Wu, Yuan Xie, Lingbo Liu, and Liang Lin, “Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(12): 9887 -9903, 2022. [PDF] [Code]

  18. Hongjun Wang, Guanbin Li, Xiaobai Liu, and Liang Lin, “A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(4): 1725-1737, 2022. [PDF]

  19. Yongsen Zheng, Pengxu Wei, Ziliang Chen, Yang Cao, and Liang Lin, “Graph-Convolved Factorization Machines for Personalized Recommendation”, IEEE Transactions on Knowledge and Data Engineering (T-KDE), 35(2): 1567 -1580, 2021. [PDF]

  20. Yukai Shi, Sen Zhang, Chenxing Zhou, Xiaodan Liang, Xiaojun Yang, and Liang Lin, “GTAE: Graph Transformer–Based Auto-Encoders for Linguistic-Constrained Text Style Transfer”, ACM Transactions on Intelligent Systems and Technology (ACM TIST), vol. 32: 1-16, 2021. [PDF] [Code]

  21. Jiangxin Dong, Jinshan Pan, Jimmy Ren, Liang Lin, Jinhui Tang, and Ming-Hsuan Yang, “Learning Spatially Variant Linear Representation Models for Joint Filtering”, IEEE Transactions on Pattern Analysis and Machine Intelligence, (T-PAMI), 44(11): 8355-8370, 2021. [PDF]

  22. Bingqian Lin, Yi Zhu, Yanxin Long, Xiaodan Liang, Qixiang Ye, and Liang Lin, “Adversarial Reinforced Instruction Attacker for Robust Vision-Language Navigation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(10): 7175 -7189, 2022. [PDF]

  23. Yang Liu, Keze Wang, Guanbin Li, and Liang Lin, “Semantics-Aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition”, IEEE Transactions on Image Processing (T-IP), vol. 30: 5573-5588, 2021. [PDF]

  24. Liang Lin, Pengxiang Yan, Xiaoqian Xu, Sibei Yang, Kun Zeng, and Guanbin Li, “Structured Attention Network for Referring Image Segmentation”, IEEE Transactions on Multimedia (T-MM), vol. 24: 1922-1932, 2021.[PDF]

  25. Changxin Huang, Ronghui Zhang, Meizi Ouyang, Pengxu Wei, Junfan Lin, Jiang Su, and Liang Lin, “Deductive Reinforcement Learning for Visual Autonomous Urban Driving Navigation”, IEEE Transactions on Neural Network and Learning Systems (T-NNLS), 32(12): 5379-5391, 2021. [PDF]

  26.  Yiming Gao, Zhanghui Kuang, Guanbin Li, Wayne Zhang, and Liang Lin, “Hierarchical Reasoning Network for Human-Object Interaction Detection”, IEEE Transactions on Image Processing (T-IP), vol.30: 8306-8317, 2021. [PDF]

  27. Guanbin Li, Pengxiang Yan, Yuan Xie, Guisheng Wang, Liang Lin, and Yizhou Yu, “Instance-Level Salient Object Segmentation”, Computer Vision and Image Understanding (CVIU), 2021. [PDF]

  28. Guangrun Wang, Liang Lin*, Rongcong Chen, Guangcong Wang, and Jiqi Zhang, “Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition”, IEEE Transactions on Neural Network and Learning Systems (T-NNLS), 33(10): 5401-5415, 2022. [PDF]

  29. Ziliang Chen, Pengxu Wei, Jingyu Zhuang, Guanbin Li, and Liang Lin, “Deep CockTail Networks: A Universal Framework for Visual Multi-source Domain Adaptation”, International Journal of Computer Vision (IJCV), 2021. [PDF]

  30. Qingxing Cao, Bailin Li, Xiaodan Liang, Keze Wang, and Liang Lin, “Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 33(7): 2758-2767, 2022. [PDF] [Dataset]

  31. Liang Lin, Yiming Gao, Ke Gong, Meng Wang, and Xiaodan Liang, “Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(5): 2504 – 2518, 2022. [PDF] [Code]

  32. Yiming Gao, Zhanghui Kuang, Guanbin Li, Ping Luo, Yimin Chen, Liang Lin, and Wayne Zhang, “Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), DOI: 10.1109/TPAMI.2020.3025062, 2020. [PDF]

  33. Tianshui Chen, Liang Lin*, Riquan Chen, Xiaolu Hui, and Hefeng Wu, “Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition”,  IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(3): 1371-1384, 2022. [PDF]

  34. Fuyu Wang, Xiaodan Liang, Lin Xu, and Liang Lin*, “Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition”, IEEE Transactions on Cybernetics (T-Cybernetics), 52(6): 5015-5025, 2022. [PDF]

  35. Junpeng Tan, Yukai Shi, Zhijing Yang, Caizhen Wen, and Liang Lin, “Unsupervised Multi-view Clustering by Squeezing Hybrid Knowledge from Cross View and Each View”, IEEE Transactions on Multimedia (T-MM), vol. 23: 2943-2956, 2020. [PDF]

  36. Haofeng Li, Yirui Zeng, Guanbin Li, Liang Lin, and Yizhou Yu, “Online Alternate Generator Against Adversarial Attacks”, IEEE Transactions on Image Processing (T-IP), vol. 29: 9305-9315, 2020. [PDF]

  37. Lingbo Liu, Jingwen Chen, Hefeng Wu, Jiajie Zhen, Guanbin Li, and Liang Lin*, “Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 23(4): 3377-3391, 2022. [PDF]

  38. Yi Zhu, Xiwen Liang, Bingqian Lin, Jianbin Jiao, Qixiang Ye, Liang Lin, and Xiaodan Liang, “Configurable Graph Reasoning for Visual Relationship Detection”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 33(1): 117-129, 2021. [PDF]

  39. Haofeng Li, Guanbin Li, Binbin Yang, Guanqi Chen, Liang Lin, and Yizhou Yu, “Depthwise Nonlocal Module for Fast Salient Object Detection Using a Single Thread”, IEEE Transactions on Cybernetics (T-Cybernetics), 51(12): 6188 -6199, 2021. [PDF]

  40. Jie Wu, Tianshui Chen, Hefeng Wu, Zhi Yang, Guangchun Luo, and Liang Lin, “Fine-Grained Image Captioning with Global-Local Discriminative Objective”, IEEE Transactions on Multimedia (T-MM), vol. 23: 2413-2427, 2021. [PDF] [Code]

  41. Guangrun Wang, Guangcong Wang, Xujie Zhang, Jianhuang Lai, and Liang Lin*, “Weakly Supervised Person Re-ID: Differentiable Graphical Learning and A New Benchmark”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 32(5): 2142-2156, 2022. [PDF] [Code with Datasets]

  42. Qingxing Cao, Xiaodan Liang, Bailin Li, and Liang Lin*, “Interpretable Visual Question Answering by Reasoning on Dependency Trees”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 43(3): 887-901, 2021. [PDF] [Code]

  43. Yukai Shi, Guanbin Li, Qingxing Cao, Keze Wang, and Liang Lin, “Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 42(11): 2809-2824, 2020. [PDF] [Code]

  44. Lingbo Liu, Jiajie Zhen, Guanbin Li, Geng Zhan, Zhaocheng He, Bowen Du, and Liang Lin, “Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020. [PDF] [Code]

  45. Xiaobai Liu, Qian Xu, Eric Medwedeff, Grayson Adkins, Liang Lin, and Shuicheng Yan, “Learning Semi-supervised Multi-Label Fully Convolutional Network for Hierarchical Object Parsing”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 31(7): 2500-2509, 2020. [PDF]

  46. Yuefang Gao, Zexi Hu, Henry W. F. Yeung, Yuk Ying Chung, Xuhong Tian, and Liang Lin, “Unifying Temporal Context and Multi-feature with Update-Pacing Framework for Visual Tracking”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 30(4): 1078-1091, 2020. [PDF] [Code]

  47. Keze Wang, Liang Lin*, Chenhan Jiang, Chen Qian, and Pengxu Wei, “3D Human Pose Machines with Self-supervised Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 42(5): 1069-1082, 2020. [PDF] [Page with Code]

  48. Lingbo Liu, Zhilin Qiu, Guanbin Li, Qing Wang, Wanli Ouyang, and Liang Lin, “Taxi Origin-Destination Demand Prediction with Contextualized Spatial-Temporal Network”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 20(10): 3875-3887, 2019. [PDF] [Code]

  49. Ruimao Zhang, Jingyu Li, Hongbin Sun, Yuying Ge, Ping Luo, Xiaogang Wang, and Liang Lin*, “SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification”, IEEE Transactions on Image Processing (T-IP), 28(10): 4870-4882, 2019. [PDF] [Code]

  50. Lingbo Liu, Guanbin Li, Yuan Xie, Yizhou Yu, Qing Wang, and Liang Lin, “Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning”, IEEE Transactions on Multimedia (T-MM), 21(9): 2248-2262, 2019. [PDF] [Page with Data]

  51. Ruimao Zhang, Wei Yang, Zhanglin Peng, Pengxu Wei, Xiaogang Wang, and Liang Lin, “Progressively Diffused Networks for Semantic Visual Parsing”, Pattern Recognition, 90(6): 78-86, 2019. [PDF]

  52. Chenglong Li, Liang Lin*, Wangmeng Zuo, Jin Tang, and Ming-Hsuan Yang, “Visual Tracking via Dynamic Graph Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 41(11): 2770-2782, 2019. [PDF]

  53. Guanbin Li, Yukang Gan, Hejun Wu, Nong Xiao, and Liang Lin*, “Cross-Modal Attentional Context Learning for RGB-D Object Detection”, IEEE Transactions on Image Processing (T-IP), 28(4): 1591-1601, 2019. [PDF]

  54. Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu, and  Liang Lin, “Neural Task Planning with And-Or Graph Representations”, IEEE Transactions on Multimedia (T-MM), 21(4):  1022-1034, 2019. [PDF]

  55. Haofeng Li, Guanbin Li, Liang Lin, Hongchuan Yu, and Yizhou Yu, “Context-Aware Semantic Inpainting” IEEE Transactions on Cybernetics (T-Cybernetics), 49(12): 4398-4411, 2019. [PDF]

  56. Keze Wang, Liang Lin*, Xiaopeng Yan, Ziliang Chen, Dongyu Zhang, and Lei Zhang, “Cost-effective Object Detection: Active Sample Mining with Switchable Selection Criteria”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 30(3): 834-850, 2019. [PDF]

  57. Xiaodan Liang, Ke Gong, Xiaohui Shen, and Liang Lin*, “Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark”,  IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 41(4): 871-885, 2019. [PDF] [Page with Code]

  58. Wangmeng Zuo, Xiaohe Wu, Liang Lin, Lei Zhang, and Ming-Hsuan Yang, “Learning Support Correlation Filters for Visual Tracking”,  IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 41(5): 1158-1172, 2019. [Project Page]

  59. Ruimao Zhang, Liang Lin*, Guangrun Wang, Meng Wang, and Wangmeng Zuo, “Hierarchical Scene Parsing by Weakly Supervised Learning with Image Descriptions”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 41(3): 596-610, 2019. [PDF] [Supplemental Material] [Page with Code]

  60. Tianshui Cheng, Liang Lin, Xian Wu, Nong Xiao, and Xiaonan Luo, “Learning to Segment Object Candidates via Recursive Neural Networks”, IEEE Transactions on Image Processing (T-IP), 27(12): 5827-5839, 2018. [PDF]

  61. Xiaobai Liu, Qian Xu, Yadong Mu, Liang Lin, Jiadi Yang, and Shuicheng Yan, “High-Precision Camera Localization in Scenes with Repetitive Patterns”, ACM Transactions on Intelligent Systems and Technology (T-IST), 9(6): Article 66, 2018. [PDF]

  62. Xiaodan Liang, Liang Lin*, Yunchao Wei, Xiaohui Shen, Jianchao Yang, and Shuicheng Yan, “Proposal-free Network for Instance-level Semantic Object Segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 40(12): 2978-2991, 2018. [PDF]

  63. Xiaohe Wu, Wangmeng Zuo, Liang Lin, Wei Jia, and David Zhang, “F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 29(11): 5185-5199, 2018. [PDF] [Code]

  64. Ziliang Chen, Keze Wang, Xiao Wang, Pai Peng, Ebroul Izquierdo, and Liang Lin*, “Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 28(10): 2667-2678, 2018. [PDF]

  65. Liang Lin, Keze Wang, Deyu Meng, Wangmeng Zuo, and Lei Zhang, “Active Self-Paced Learning for Cost-Effective and Progressive Face Identification”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 40(1): 7-19, 2018.  [PDF] [Page with Code]

  66. Wangmeng Zuo, Faqiang Wang, David Zhang, Liang Lin, Yuchi Huang, Deyu Meng, and Lei Zhang, “Distance Metric Learning via Iterated Support Vector Machines”, IEEE Transactions on Image Processing (T-IP), 26(10): 4937-4950, 2017. [PDF]

  67. Yukai Shi, Keze Wang, Chongyu Chen, Li Xu, and Liang Lin, “Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning”, IEEE Transactions on Multimedia (T-MM), 19(12): 2804-2815, 2017. [PDF]

  68. Jun Zhang, Meng Wang, Liang Lin, Xun Yang, Jun Gao, and Yong Rui, “Saliency Detection on Light Field: A Multi-Cue Approach”, ACM Transactions on Multimedia Computing, Communications, and Applications (ACM-TOMM), 13(3): Article 32, 2017. [PDF]

  69. Xiaodan Liang, Chunyan Xu, Xiaohui Shen, Jianchao Yang, Jinhui Tang, Liang Lin*, Shuicheng Yan, “Human Parsing with Contextualized Convolutional Neural Network”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(1): 115-127, 2017. [PDF]

  70. Dongyu Zhang, Liang Lin*, Tianshui Chen, Xian Wu, Wenwei Tan, and Ebroul Izquierdo, “Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning”, IEEE Transactions on Image Processing (T-IP), 26(1): 328-339, 2017.  [PDF] [Page with Code]

  71. Keze Wang, Dongyu Zhang, Ya Li, Ruimao Zhang, and Liang Lin, “Cost-Effective Active Learning for Deep Image Classification”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 27(12): 2591-2600, 2017. [PDF]

  72. Liang Lin, Guangrun Wang, Wangmeng Zuo, Xiangchu Feng, and Lei Zhang, “Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(6): 1089-1102, 2017. [PDF] [Page with Code]

  73. Xiaodan Liang, Yunchao Wei, Liang Lin*, Yunpeng Chen, Xiaohui Shen, Jianchao Yang, and Shuicheng Yan, “Learning to Segment Human by Watching Youtube”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(7): 1462-1468, 2017. [PDF]

  74. Chenglong Li, Xiao Wang, Lei Zhang, Jin Tang, Hejun Wu, Liang Lin*, “WELD: Weighted Low-rank Decomposition for Robust Grayscale-Thermal Foreground Detection”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 27(4): 725-738, 2017. [PDF] [Page with Code]

  75. Chenglong Li, Hui Cheng, Shiyi Hu, Xiaobai Liu, Jin Tang, and Liang Lin, “Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking”, IEEE Transactions on Image Processing (T-IP), 25(12): 5743-5756, 2016. [PDF]

  76. Liang Lin, Keze Wang, Wangmeng Zuo, Meng Wang, Jiebo Luo, and Lei Zhang, “A Deep Structured Model with Radius-Margin Bound for 3D Human Activity Recognition”, International Journal of Computer Vision (IJCV), 118(2): 256-273, 2016. [PDF] [Code]

  77. Ping Luo, Liang Lin*, and Xiaobai Liu, “Learning Compositional Shape Models of Multiple Distance Metrics by Information Projection”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 27(7): 1417-1428, 2016. [PDF]

  78. Liang Lin, Wei Yang, Chenglong Li, Jin Tang, and Xiaochun Cao, “Inference With Collaborative Model for Interactive Tumor Segmentation in Medical Image Sequences”, IEEE Transactions on Cybernetics (T-Cybernetics), 46(12): 2796-2809, 2016. [PDF] [Page with Data]

  79. Tianshui Chen, Liang Lin*, Lingbo Liu, Xiaonan Luo, and Xuelong Li, “DISC: Deep Image Saliency Computing via Progressive Representation Learning”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 27(6): 1135-1149, 2016. [PDF] [Page with Code]

  80. Xiaodan Liang, Liang Lin*, Wei Yang, Ping Luo, Junshi Huang, and Shuicheng Yan, “Clothes Co-Parsing via Joint Image Segmentation and Labeling with Application to Clothing Retrieval”, IEEE Transactions on Multimedia (T-MM), 18(6): 1175-1186, 2016. [PDF] [Page with Code]

  81. Liang Lin, Yongyi Lu, Chenglong Li, Hui Cheng, and Wangmeng Zuo, “Detection-free Multi-object Tracking by Reconfigurable Inference with Bundle Representations”, IEEE Transactions on Cybernetics (T-Cybernetics), 46(11): 2447-2458, 2016. [PDF]

  82. Chenglong Li, Liang Lin*, Wangmeng Zuo, Wenzhong Wang, and Jin Tang, “An Approach to Streaming Video Segmentation with Sub-optimal Low-rank Decomposition”, IEEE Transactions on Image Processing (T-IP), 25(5): 21947-1960, 2016. [PDF] [Page with Code]

  83. Xiaodan Liang, Liang Lin*, Qingxing Cao, Rui Huang, and Yongtian Wang, “Recognizing Focal Liver Lesions in CEUS with Dynamically Trained Latent Structured Models”, IEEE Transactions on Medical Imaging (T-MI), 35(3): 713-727, 2016. [PDF][Page with Code]

  84. Zhanglin Peng, Ya Li, Zhaoquan Cai, and Liang Lin*, “Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy”, Neurocomputing, 178: 36-45, 2016. [PDF]

  85. Ruimao Zhang, Liang Lin*, Rui Zhang, Wangmeng Zuo, and Lei Zhang, “Bit-Scalable Deep Hashing with Regularized Similarity Learning for Image Retrieval and Person Re-identification”, IEEE Transactions on Image Processing (T-IP), 24(12): 4766-4779, 2015. [PDF]

  86. Xionghao Liu, Wei Yang, Liang Lin, Qing Wang, Zhaoquan Cai, Jian-Huang Lai, “Data-Driven Scene Understanding with Adaptively Retrieved Exemplars”, IEEE Multimedia (MM), 22(3): 82-92, 2015. [PDF]

  87. Si Liu, Xiaodan Liang, Luoqi Liu, Ke Lu, Liang Lin, Xiaochun Cao, and Shuicheng Yan, “Fashion  Parsing with Video Context”, IEEE Transactions on Multimedia (T-MM), 17(8): 1347-1358, 2015. [PDF]

  88. Keze Wang, Liang Lin*, Jiangbo Lu, Chenglong Li, and Keyang Shi, “PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence”, IEEE Transactions on Image Processing (T-IP), 24(10): 3019-3033, 2015. [PDF]

  89. Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Liang Lin, and Shuicheng Yan, “Deep Human Parsing with Active Template Regression”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 37(12): 2402-2414, 2015. [PDF]

  90. Shengyong Ding, Liang Lin*, Guangrun Wang, and Hongyang Chao, “Deep Feature Learning with Relative Distance Comparison for Person Re-identification”,Pattern Recognition, 48(10): 2993-3003, 2015. [PDF] (Best Paper Award)

  91. Zhihua Chen, Wangmeng Zuo, Qinghua Hu, and Liang Lin, “Kernel Sparse Representation for Time Series Classification”, Information Sciences, 292(20): 15-26, 2015. [PDF]

  92. Liang Lin, Xiaolong Wang, Wei Yang, and JianHuang Lai, “Discriminatively Trained And-Or Graph Models for Object Shape Detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 37(5): 959-972, 2015. [PDF]

  93. Ning Liu, Hefeng Wu, and Liang Lin, “Hierarchical Ensemble of Background Models for PTZ-based Video Surveillance”, IEEE Transactions on Cybernectics (T-Cybernetics), 45(1): 89-102, 2015. [PDF]

  94. Liang Lin, Ruimao Zhang, and Xiaohua Duan, “Adaptive Scene Category Discovery with Generative Learning and Compositional Sampling”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 25(2): 251-260, 2015. [PDF]

  95. Bo Jiang, Jin Tang, Bin Luo, and Liang Lin, “Robust Feature Point Matching with Sparse Model”, IEEE Transactions on Image Processing (T-IP), 23(12): 5175-5186, 2014. [PDF]

  96. Liang Lin, Yuanlu Xu, Xiaodan Liang, and Jianhuang Lai, “Complex Background Subtraction by Pursuing Dynamic Spatio-Temporal Models”, IEEE Transactions on Image Processing (T-IP), 23(7): 3191-3202, 2014. [PDF]

  97. Xiaobai Liu, Liang Lin*, and Hai Jin, “Contextualized Trajectory Parsing with Spatio-Temporal Graph”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 35(12): 3010-3024, 2013. [PDF]

  98. Liang Lin, Kun Zeng, Yizhou Wang, Ying-Qing Xu, and Song-Chun Zhu, “Video Stylization: Painterly Rendering and Optimization with Content Extraction”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 23(4): 577-590, 2013. [PDF]

  99. Hanjiang Lai, Yan Pan, Cong Liu, Liang Lin, and Jie Wu, “Sparse Learning-to-Rank via an Efficient Primal-Dual Algorithm”, IEEE Transactions on Computers (T-Computers), 62(6): 1221-1233, 2013. [PDF]

  100. Xiaohua Duan, Liang Lin*, and Hongyang Chao, “Discovering Video Shot Categories by Unsupervised Stochastic Graph Partition”, IEEE Transactions on Multimedia (T-MM), 15(1): 167-180, 2013. [PDF]

  101. Liang Lin, Yongyi Lu, Yan Pan, and Xiaowu Chen, “Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance”, IEEE Transactions on Image Processing (T-IP), 21(12): 4844-4857, 2012. [PDF]

  102. Liang Lin, Xiaobai Liu, Shaowu Peng, Hongyang Chao, Yongtian Wang, and Bo Jiang, “Object Categorization with Sketch Representation and Generalized Samples”, Pattern Recognition, 45(10): 3648-3660, 2012. [PDF]

  103. Xiaobai Liu, Liang Lin*, Hai Jin, Shuicheng Yan, and Wenbin Tao, “Integrating Spatio-temporal Context with Multiview Representation for Object Recognition in Visual Surveillance”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 21(4): 393-407, 2011. [PDF]

  104. Liang Lin, Ping Luo, Xiaowu Chen, and Kun Zeng, “Representing and Recognizing Objects with Massive Local Image Patches”, Pattern Recognition, 45(1): 231-240, 2012. [PDF]

  105. Xiaobai Liu, Liang Lin*, Shuicheng Yan, Hai Jin, and Wenbing Jiang, “Adaptive Object Tracking by Learning Hybrid Template On-line”, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 21(11): 1588-1599, 2011. [PDF]

  106. Jinli Suo, Liang Lin, Shiguang Shan, Xilin Chen, and Wen Gao, “High Resolution Face Fusion for Gender Conversion”, IEEE Transactions on Systems, Man, and Cybernetics (T-SMC), Part A, 41(2): 226-237, 2011. [PDF]

  107. Liang Lin, Xiaobai Liu, and Song-Chun Zhu, “Layered Graph Matching with Composite Cluster Sampling”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 32(8): 1426-1442, 2010. [PDF]

  108. Benjamin Yao, Xiong Yang, Liang Lin, M.W. Lee, and Song-Chun Zhu, “I2T: Image Parsing to Text Description”, Proceedings of the IEEE, 98(8): 1485-1508, 2010. [PDF]

  109. Liang Lin, Tianfu Wu, Jake Porway, and Zijian Xu, “A Stochastic Graph Grammar for Compositional Object Representation and Recognition”, Pattern Recognition, 42(7): 1297-1307, 2009. [PDF]

  110. Liang Lin, Haifeng Gong, Li Li, and Liang Wang, “Semantic Event Representation and Recognition Using Syntactic Attribute Graph Grammar”, Pattern Recognition Letters, 30(2): 180-186, 2009. [PDF]

  111. Liang Lin, Kun Zeng, Yongtian Wang, and Wenze Hu, “3D Structure Inference by Integrating Segmentation and Reconstruction from A Single Image”, IET Computer Vision, 2(1): 15-22, 2008. [PDF]

  112. Liang Lin, Yongtian Wang, Yue Liu, Caiming Xiong and Kun Zeng, “Marker-less Registration Based on Template Tracking for Augmented Reality”, Multimedia Tools and Applications Journal (MMTA), 41(2): 235-252, 2009. [PDF]

  113. Liang Lin, Yue Liu, Yongtian Wang, and Wei Zheng, “Registration Algorithm Based on Image Matching for Outdoor AR System with Fixed Viewing Position”, IEE Proceedings on Vision, Image & Signal Processing, 153(1): 57-62, 2006. [PDF]

Selected Conference Papers    (* indicates I am the paper’s corresponding author)

  1. Yao Xiao, Ziyi Tang, Pengxu Wei, Cong Liu, and Liang Lin, “Masked Images Are Counterfactual Samples for Robust Fine-tuning”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [PDF]

  2. Weizhi Zhong, Chaowei Fang, Yinqi Cai, Pengxu Wei, Gangming Zhao, Liang Lin, and Guanbin Li, “Identity-Preserving Talking Face Generation with Landmark and Appearance Priors”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [PDF]

  3. Junfan Lin, Jianlong Chang, Lingbo Liu, Guanbin Li, Liang Lin, Qi Tian3, and Chang Wen Chen, “Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [PDF] (Oral Representation)

  4. Bingqian Lin, Yi Zhu, Xiaodan Liang, Liang Lin, and Jianzhuang Liu, “Actional Atomic-Concept Learning for Demystifying Vision-Language Navigation”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2023. [PDF]

  5. Yang Wu, Pengxu Wei, and Liang Lin, “Scene Graph to Image Synthesis via Knowledge Consensus”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2023. [PDF]

  6. Yuxiang Nie, Chaowei Fang, Lechao Cheng, Liang Lin, and Guanbin Li, “Adapting Object Size Variance and Class Imbalance for Semi-Supervised Object Detection”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2023. [PDF]

  7. KuoWang, Jingyu Zhuang, Guanbin Li, Chaowei Fang, Lechao Cheng, Liang Lin, and Fan Zhou, “De-biased Teacher: Rethinking IoU Matching for Semi-Supervised Object Detection”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2023. [PDF]

  8. Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip H. S. Torr2, Liang Lin*, “Structure-Preserving 3D Garment Modeling with Neural Sewing Machines”, Proc. of Advances in Neural Information Processing Systems (NeurlPS), 2022. [PDF]

  9. Ziyi Zhang, Weikai Chen, Hui Cheng, Zhen Li, Siyuan Li, Liang Lin, and Guanbin Li, “Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning”, Proc. of Advances in Neural Information Processing Systems (NeurlPS), 2022. [PDF]

  10. Ziyi Dong, Pengxu Wei, and Liang Lin, “Adversarially-Aware Robust Object Detector”, Proc. of European Conference on Computer Vision (ECCV), 2022. [PDF] (Oral Representation)

  11. Pengxiang Yan, Ziyi Wu, Mengmeng Liu, Kun Zeng, Liang Lin, and Guanbin Li, “Unsupervised Domain Adaptive Salient Object Detection Through Uncertainty-Aware Pseudo-Label Learning”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2022. [PDF]

  12. Tianshui Chen, Tao Pu, Hefeng Wu, Yuan Xie, and Liang Lin*, “Structured Semantic Transfer for Multi-Label Recognition with Partial Labels”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2022. [PDF]

  13. Tao Pu, Tianshui Chen, Hefeng Wu, and Liang Lin*, “Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2022. [PDF]

  14. Binbin Yang, Xinchi Deng, Han Shi, Changlin Li, Gengwei Zhang, Hang Xu, Shen Zhao, Liang Lin*, and Xiaodan Liang, “Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [PDF]

  15. Guangrun Wang, Yansong Tang, Liang Lin, and Philip H.S. Torr, “Semantic-Aware Auto-Encoders for Self-supervised Representation Learning”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [PDF]

  16. Xiaoqian Xu, Pengxu Wei, Weikai Chen, Yang Liu, Mingzhi Mao, Liang Lin, and Guanbin Li, “Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [PDF] (Oral Representation)

  17. Zhongzhan Huang, Wenqi Shao, Xinjiang Wang, Liang Lin, and Ping Luo, “Rethinking the Pruning Criteria for Convolutional Neural Network”, Proc. of Advances in Neural Information Processing Systems (NeurlPS), 2021. [PDF]

  18. Jinghui Qin, Xiaodan Liang, Yining Hong, Jianheng Tang, and Liang Lin*, “Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks”, The Joint Conference of Annual Meeting of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021. (Oral Presentation) [PDF]

  19. Zheng Ye, Liucun Lu, Lishan Huang, Liang Lin, and Xiaodan Liang, “Towards Quantifiable Dialogue Coherence Evaluation”, The Joint Conference of Annual Meeting of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021.

  20. Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric Xing, and Liang Lin, “GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning”, The Joint Conference of Annual Meeting of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021.

  21. Shuai Lin, Pan Zhou, Xiaodan Liang, Jianheng Tang, Ruihui Zhao, Ziliang Chen, and Liang Lin, “Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation”,  Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2021. [PDF]

  22. Xipeng Chen, Pengxu Wei, and Liang Lin, “Deductive Learning for Weakly-Supervised 3D Human Pose Estimation via Uncalibrated Cameras”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2021. [PDF]

  23. Yubei Xiao, Ke Gong, Pan Zhou, Guolin Zheng, Xiaodan Liang, and Liang Lin*, “Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2021. [PDF]

  24. Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, and Liang Lin*, “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [PDF]

  25. Junfan Lin, Zhongzhan Huang, Keze Wang, Xiaodan Liang, Weiwei Chen, and Liang Lin, “Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), 2021.

  26. Tao Pu, Tianshui Chen, Yuan Xie, Hefeng Wu, and Liang Lin, “AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), 2021.

  27. Jiutao Yue, Haofeng Li, Pengxu Wei, Guanbin Li, and Liang Lin, “Robust Real-World Image Super-Resolution against Adversarial Attacks”, Proc. ACM International Conference on Multimedia (ACM MM), 2021. [PDF]

  28. Junkai Huang, Chaowei Fang, Weikai Chen, Zhenhua Chai, Xiaolin Wei, Pengxu Wei, Liang Lin, and Guanbin Li, “Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2021. [PDF]

  29. Jiefeng Peng, Jiqi Zhang, Changlin Li, Guangrun Wang, Xiaodan Liang, and Liang Lin, “Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2021. [PDF]

  30. Qingxing Cao, Wentao Wan, Keze Wang, Xiaodan Liang, and Liang Lin*, “Linguistically Routing Capsule Network for Out-of-distribution Visual Question Answering”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2021. [PDF]

  31. Guangrun Wang, Keze Wang, Guangcong Wang, Philip H.S. Torr, and Liang Lin*, “Solving Inefficiency of Self-supervised Representation Learning”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2021. [PDF]

  32. Jie Wu, Wei Zhang, Guanbin Li, Wenhao Wu, Xiao Tan, Yingying Li, Errui Ding, Liang Lin, “Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2021. [PDF]

  33. Yangxin Wu, Gengwei Zhang, Hang Xu, Xiaodan Liang, and Liang Lin*, “Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation”, Proc. of Advances in Neural Information Processing Systems (NeurlPS), 2020. [PDF]

  34. Lingbo Liu, Jiaqi Chen, Hefeng Wu, Tianshui Chen, Guanbin Li, and Liang Lin, “Efficient Crowd Counting via Structured Knowledge Transfer”, Proc. ACM International Conference on Multimedia (ACM MM), 2020. [PDF]

  35. Yuan Xie, Tianshui Chen, Tao Pu, Hefeng Wu, and Liang Lin, “Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition”, Proc. ACM International Conference on Multimedia (ACM MM), 2020. [PDF]

  36. Jie Wu, Guanbin Li, Xiaoguang Han, and Liang Lin, “Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos”, Proc. ACM International Conference on Multimedia (ACM MM), 2020. [PDF]

  37. Jie Wu, Tianshui Chen, Lishan Huang, Hefeng Wu, Guanbin Li, Ling Tian, and Liang Lin, “Active Object Search”,  Proc. ACM International Conference on Multimedia (ACM MM), 2020. [PDF]

  38. Lishan Huang, Zheng Ye, Jinghui Qin, Liang Lin, and Xiaodan Liang, “GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems”, Prof. of Conference on Empirical Methods in Natural Language Processing (EMMNLP), 2020. [PDF]

  39. Jinghui Qin, Lihui Lin, Xiaodan Liang, Rumin Zhang, and Liang Lin, “Semantically-Aligned Universal Tree-Structured Solver for Math Word Problems”, Prof. of Conference on Empirical Methods in Natural Language Processing (EMMNLP), 2020. [PDF]

  40. Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, and Liang Lin*, “Component Divide-and-Conquer for Real-World Image Super-Resolution”, Proc. of European Conference on Computer Vision (ECCV), 2020. (Oral Presentation) [PDF]

  41. Bailin Li, Bowen Wu, Jiang Su, Guangrun Wang, and Liang Lin, “EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning”, Proc. of European Conference on Computer Vision (ECCV), 2020. (Oral Presentation) [PDF] [Code]

  42. Guangrun Wang, Guangcong Wang, Keze Wang, Xiaodan Liang, and Liang Lin*, “Grammatically Recognizing Images with Tree Convolution”, Proc. of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020. [PDF] [Code]

  43. Yangxin Wu, Gengwei Zhang, Yiming Gao, Xiajun Deng, Ke Gong, Xiaodan Liang, and Liang Lin, “Bidirectional Graph Reasoning Network for Panoptic Segmentation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [PDF]

  44. Hongjun Wang, Guangrun Wang, Ya Li, Dongyu Zhang, and Liang Lin*, “Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification with Deep Mis-Ranking”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Oral Representation) [PDF] [Code]

  45. Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang, Xiaodan Liang, Liang Lin, and Xiaochun Chang, “Block-wisely Supervised Neural Architecture Search with Knowledge Distillation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [PDF] [Report] [Code and Models]

  46. Jie Wu, Guanbin Li, Si Liu, and Liang Lin, “Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2020. [PDF] [Code]

  47. Jihan Yang, Ruijia Xu, Ruiyu Li, Xiaojuan Qi, Xiaoyong Shen, Guanbin Li, and Liang Lin, “An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2020. [PDF]

  48. Riquan Chen, Tianshui Chen, Xiaolu Hui, Hefeng Wu, Guanbin Li, and Liang Lin, “Knowledge Graph Transfer Network for Few-Shot Recognition”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2020. [PDF] (Oral Presentation)

  49. Wei Zhang, Guanbin Li, Fuyu Wang, Longjiang E, Yizhou Yu, Liang Lin, and Huiying Liang, “Simultaneous Lung Field Detection and Segmentation for Pediatric Chest Radiographs”, Proc. of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. [PDF]

  50. Lingbo Liu, Zhilin Qiu, Guanbin Li, Shufan Liu, Wanli Ouyang, and Liang Lin*, “Crowd Counting with Deep Structured Scale Integration Network”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]

  51. Zhanghui Kuang, Yiming Gao, Guanbin Li, Ping Luo, Yimin Chen, Liang Lin, and Wayne Zhang, “Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]

  52. Ruijia Xu, Guanbin Li, Yihan Yang, and Liang Lin, “Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]  (Best Paper Nomination, only one candidate from China)

  53. Xiaopeng Yan, Ziliang Chen, Anni Xu, Xiaoxi Wang, Xiaodan Liang, and Liang Lin*, “Meta R-CNN : Towards General Solver for Instance-level Low-shot Learning”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]

  54. Tianshui Chen, Muxin Xu, Xiaolu Hui, Hefeng Wu, and Liang Lin, “Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]

  55. Pengxiang Yan, Guanbin Li, Yuan Xie, Zhen Li, Chuan Wang, Tianshui Chen, and Liang Lin, “Semi-Supervised Video Salient Object Detection Using Pseudo-Labels”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. [PDF]

  56. Hongjun Wang, Guangrun Wang, Guanbin Li, and Liang Lin, “CamDrop: A New Explanation of Dropout and A Guided Regularization Method for Deep Neural Networks”, ACM International Conference on Information and Knowledge Management (CIKM), 2019. [PDF]

  57. Ziliang Chen, Zhanfu Yang, Xiaoxi Wang, Xiaodan Liang, Xiaopeng Yan, Guanbin Li, and Liang Lin*, “Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching”, International Conference on Machine Learning (ICML), 2019. [PDF]

  58. Guangrun Wang, Keze Wang, and Liang Lin*, “Adaptively Connected Neural Networks”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF] [Code]

  59. Xipeng Chen, Kwan-Yee Lin, Wentao Liu, Chen Qian, and Liang Lin*, “Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  60. Ziliang Chen, Jingyu Zhuang, Xiaodan Liang, and Liang Lin*, “Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  61. Weijiang Yu, Xiaodan Liang, Ke Gong, Chenhan Jiang, Nong Xiao, and Liang Lin, “Layout-Graph Reasoning for Fashion Landmark Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  62. Hang Xu, Chenhan Jiang, Xiaodan Liang, Liang Lin, and Zhenguo Li, “Reasoning-RCNN: Unifying Adaptive Global Reasoning into Large-scale Object Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  63. Tianshui Chen, Weihao Yu, Riquan Chen, and Liang Lin*, “Knowledge-Embedded Routing Network for Scene Graph Generation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF] [Code]

  64. Ke Gong, Yiming Gao, Xiaodan Liang, Xiaohui Shen, Meng Wang, and Liang Lin, “Graphonomy: Universal Human Parsing via Graph Transfer Learning”,  Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  65. Jinshan Pan, Jiangxin Dong, Jimmy Ren, Liang Lin, Jinhui Tang, and Ming-Hsuan, “Spatially Variant Linear Representation Models for Joint Filtering”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  66. Chao Chen, Guanbin Li, Ruijia Xu, Tianshui Chen, Meng Wang, and Liang Lin, “CluterNet: Deep Hierarchical Cluster Network with Rigorously Rotation-Invariant Representation for Point Cloud Analysis”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF]

  67. Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin, “SNAS: Stochastic Neural Architecture Search”, International Conference on Learning Representations (ICLR), 2019. [PDF]

  68. Sirui Xie, Junning Huang, Lanxin Lei, Chunxiao Liu, Zheng Ma, Wei Zhang, and Liang Lin, “NADPEx: An On-policy Temporally Consistent Exploration Method for Deep Reinforcement Learning”, International Conference on Learning Representations (ICLR), 2019. [PDF]

  69. Lili Huang, Ya Li, Guanbin Li, and Liang Lin, “Lightweight Contrast Modeling for Attention-Aware Visual Localization”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), 2019. [PDF]

  70. Lin Xu, Qixian Zhou, Ke Gong, Xiaodan Liang, Jianheng Tang, and Liang Lin, “End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2019. (Oral Presentation) [PDF]

  71. Guanbin Li, Xin Zhu, Yirui Zeng, Qing Wang, and Liang Lin, “Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2019. (Oral Presentation) [PDF]

  72. Xu Cai, Yang Wu, Guanbin Li, Ziliang Chen, and Liang Lin*, “FRAME Revisited: An Interpretation View Based on Particle Evolution”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2019. (Oral Presentation) [PDF] [Code]

  73. Chenhan Jiang, Hang Xu, Xiaodan Liang, and Liang Lin, “Hybrid Knowledge Routed Modules for Large-scale Object Detection”, Proc. of Advances in Neural Information Processing Systems (NIPS), 2018. [PDF]

  74. Guangrun Wang, Jiefeng Peng, Ping Luo, Xinjiang Wang, and Liang Lin*, “Kalman Normalization: Normalizing Internal Representations Across Network Layers”, Proc. of Advances in Neural Information Processing Systems (NIPS), 2018. [PDF] [Code]

  75. Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, and Eric P. Xing, “Symbolic Graph Reasoning Meets Convolutions”, Proc. of Advances in Neural Information Processing Systems (NIPS), 2018. [PDF]

  76. Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo, and Liang Lin*, “Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding”, Proc. ACM International Conference on Multimedia (ACM MM), 2018. [PDF]

  77. Qixian Zhou, Xiaodan Liang, Ke Gong, and Liang Lin, “Adaptive Temporal Encoding Network for Video Instance-level Human Parsing”, Proc. ACM International Conference on Multimedia (ACM MM), 2018. [PDF]

  78. Tingting Li, Ruihe Qian, Chao Dong, Si Liu, Qiong Yan, Wenwu Zhu, and Liang Lin, “BeautyGAN: Instance-level Facial Makeup Transfer with Deep Generative Adversarial Network”, Proc. ACM International Conference on Multimedia (ACM MM), 2018. [PDF]

  79. Guanbin Li, Xiang He, Wei Zhang, Huiyou Chang, Le Dong, and Liang Lin, “Non-locally Enhanced Encoder-Decoder Network for Single Image De-raining”, Proc. ACM International Conference on Multimedia (ACM MM), 2018. [PDF]

  80. Lingbo Liu, Ruimao Zhang, Jiefeng Peng, Guanbin Li, Bowen Du, and Liang Lin, “Attentive Crowd Flow Machines”, Proc. ACM International Conference on Multimedia (ACM MM), 2018. [PDF]

  81. Xiaoming Li, Ming Liu, Yuting Ye, Wangmeng Zuo, Liang Lin, and Ruigang Yang, “Learning Warped Guidance for Blind Face Restoration”, Proc. of European Conference on Computer Vision (ECCV), 2018. [PDF]

  82. Xiaodan Liang, Hao Zhang, Liang Lin, and Eric Xing, “Generative Semantic Manipulation with Mask-Contrasting GAN”, Proc. of European Conference on Computer Vision (ECCV), 2018. [PDF]

  83. Yukang Gan, Xiangyu Xu, Wenxiu Sun, and Liang Lin, “Monocular Depth Estimation with Affinity, Vertical Pooling, and Label Enhancement”, Proc. of European Conference on Computer Vision (ECCV), 2018. [PDF]

  84. Ke Gong, Xiaodan Liang, Yicheng Li, Yimin Chen, Ming Yang, and Liang Lin, “Instance-level Human Parsing via Part Grouping Network”, Proc. of European Conference on Computer Vision (ECCV), 2018.[PDF]

  85. Bochao Wang, Huabin Zheng, Xiaodan Liang, Yimin Chen, Liang Lin, and Meng Yang, “Toward Characteristic-Preserving Image-based Virtual Try-On Network”, Proc. of European Conference on Computer Vision (ECCV), 2018. [PDF]

  86. Keze Wang, Liang Lin*, Chuangjie Ren, Wei Zhang, and Wenxiu Sun, “Convolutional Memory Blocks for Depth Data Representation Learning”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. [PDF] [Page with Code]

  87. Lingbo Liu, Hongjun Wang, Guanbin Li, Wanli Ouyang, and Liang Lin, “Crowd Counting using Deep Recurrent Spatial-Aware Network”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. [PDF]

  88. Min Wang, Xipeng Chen, Wentao Liu, Chen Qian, Liang Lin, and Lizhuang Ma, “DRPose3D: Depth Ranking in 3D Human Pose Estimation”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. [PDF]

  89. Zhouxia Wang, Tianshui Chen, Jimmy Ren, Weihao Yu, Hui Cheng, and Liang Lin*, “Deep Reasoning with Knowledge Graph for Social Relationship Understanding”,  Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. [PDF]

  90. Tianshui Chen, Liang Lin*, Riquan Chen, Yang Wu, and Xiaonan Luo, “Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. [PDF]

  91. Keze Wang, Xiaopeng Yan, Dongyu Zhang, Lei Zhang, and Liang Lin, “Towards Human-Machine Cooperation:  Self-supervised Sample Mining for Object Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  92. Yue Luo, Jimmy Ren, Zhouxia Wang, Wenxiu Sun, Jinshan Pan, Jianbo Liu, Jiahao Pang, and Liang Lin, “LSTM Pose Machines”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  93. Guanbin Li, Yuan Xie, Tianhao Wei, Keze Wang, and Liang Lin*, “Flow Guided Recurrent Neural Encoder for Video Salient Object Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  94. Xian Wu, Guanbin Li, Qingxing Cao, Qingge Ji, and Liang Lin, “Interpretable Video Captioning via Trajectory Structured Localization”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  95. Qingxing Cao, Xiaodan Liang, Bailin Li, Guanbin Li, and Liang Lin*, “Visual Question Reasoning on General Dependency Tree”,  Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  96. Ruijia Xu, Ziliang Chen, Wangmeng Zuo, Junjie Yan, and Liang Lin*, “Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF] [Supp.]

  97. Ke Yu, Chao Dong, Liang Lin, and Chen Change Loy, “Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  98. Jiahao Pang, Wenxiu Sun, Chengxi Yang, Jimmy Ren, Ruichao Xiao, Jin Zeng, and Liang Lin, “Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF] [Supp.]

  99. Yue Luo, Jimmy Ren, Mude Lin, Jiahao Pang, Wenxiu Sun, Hongsheng Li, and Liang Lin, “Single View Stereo Matching”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

  100. Hui Cheng, Junhao Cai, Quande Liu, Zhanpeng Zhang, Kai Yang, Chen Change Loy, and Liang Lin, “Fusing Object Context to Detect Functional Area for Cognitive Robots”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), 2018.

  101. Zhongchang Liu, Zeyu Jiang, Tianye Xu, Hui Cheng, Zhipeng Xie, and Liang Lin, “Avoidance of High-speed Obstacles Based on Velocity Obstacles”, Proc. of IEEE International Conference on Robotics and Automation (ICRA), 2018.

  102. Tianshui Chen, Liang Lin*, Wangmeng Zuo, Xiaonan Luo, and Lei Zhang, “Learning A Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2018. (Oral Presentation) [PDF] [Page with Code]

  103. Guanbin Li, Yuan Xie, and Liang Lin*, “Weakly Supervised Salient Object Detection Using Image Labels”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2018. (Oral Presentation) [PDF]

  104. Tianshui Chen, Zhouxia Wang, Guanbin Li, and Liang Lin, “Attentional Reinforcement Learning for Multi-label Image Recognition”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2018.  [PDF]

  105. Hui Cheng, Zhuoqi Zheng, Jinhao He, Chongyu Chen, Keze Wang, and Liang Lin, “Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry”, Proc. of IEEE\RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. [PDF]

  106. Liang Lin, Lili Huang, Tianshui Chen, Yukang Gan, and Hui Cheng, “Knowledge-Guided Recurrent Neural Network Learning for Task-oriented Action Prediction”, Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2017.  (The world’s first 10K Best Paper Diamond Award, More info: http://www.ieee-icme.org/sc/award.php) [PDF]

  107. Zhouxia Wang, Tianshui Chen, Guanbin Li, Ruijia Xu, and Liang Lin*, “Multi-label Image Recognition by Recurrently Discovering Attentional Regions”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2017. [PDF]

  108. Ping Luo, Guangrun Wang, Liang Lin*, and Xiaogang Wang, “Deep Dual Learning for Semantic Image Segmentation”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2017. [PDF]

  109. Xiaobai Liu, Qi Chen, Yuanlu Xu, and Liang Lin, “Place-centric Visual Urban Perception with Deep Multi-instance Regression”, Proc. of ACM International Conference on Multimedia (ACM MM), 2017. [PDF]

  110. Hui Cheng, Qiyuan Zhu, Zhongchang Liu, Tianye Xu, and Liang Lin, “Decentralized Navigation of Multiple Agents Based on ORCA and Model Predictive Control”, Proc. of IEEE\RSJ International Conference on Intelligent Robots and Systems (IROS), 2017. [PDF]

  111. Qingxing Cao, Liang Lin*, Yukai Shi, Xiaodan Liang, and Guanbin Li, “Attention-Aware Face Hallucination via Deep Reinforcement Learning”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  112. Mude Lin, Liang Lin*, Xiaodan Liang, Keze Wang, and Hui Cheng, “Recurrent 3D Pose Sequence Machines”,  of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  113. Ke Gong, Xiaodan Liang, Dongyu Zhang, Xiaohui Shen, and Liang Lin, “Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing”,  Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  114. Xiaodan Liang, Liang Lin*, Xiaohui Shen, Jiashi Feng, Shuicheng Yan, and Eric Xing, “Interpretable Structure-Evolving LSTM”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  115. Guanbin Li, Yuan Xie, Liang Lin, and Yizhou Yu, “Instance-Level Salient Object Segmentation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  116. Tong Xiao, Shuang Li, Bochao Wang, Liang Lin, and Xiaogang Wang, “Joint Detection and Identification Feature Learning for Person Search”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF][Page with Code]

  117. Guangrun Wang, Ping Luo, Liang Lin*, and Xiaogang Wang, “Learning Object Interactions and Descriptions for Semantic Image Segmentation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF]

  118. Chenglong Li, Liang Lin*, Wangmeng Zuo, and Jin Tang, “Learning Patch-based Dynamic Graph for Visual Tracking”,  Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2017. (Oral Presentation) [PDF]

  119. Keze Wang, Shengfu Zhai, Hui Cheng, Xiaodan Liang, and Liang Lin, “Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning”, Proc. of ACM International Conference on Multimedia (ACM MM), (full paper, Oral Presentation), 2016. [PDF]

  120. Zhen Li, Yukang Gan, Xiaodan Liang, Yizhou Yu, Hui Cheng, and Liang Lin*, “LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling”, Proc. of European Conference on Computer Vision (ECCV), 2016. [PDF]

  121. Xiaodan Liang, Xiaohui Shen, Jiashi Feng, Liang Lin*, and Shuicheng Yan, “Semantic Object Parsing with Graph LSTM”,  Proc. of European Conference on Computer Vision (ECCV), 2016. [PDF]

  122. Liliang Zhang, Liang Lin*, Xiaodan Liang, Kaiming He, “Is Faster R-CNN Doing Well for Pedestrian Detection?”, Proc. of European Conference on Computer Vision (ECCV), 2016. [PDF] [Page with Code]

  123. Xiaobai Liu, Yadong Mu, and Liang Lin, “A Stochastic Image Grammar for Fine-grained 3D Scene Reconstruction”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2016. [PDF]

  124. Zhanglin Peng, Ruimao Zhang, Xiaodan Liang, Xiaobai Liu, and Liang Lin*, “Geometric Scene Parsing with Hierarchical LSTM”, Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2016. [PDF]

  125. Yukai Shi, Keze Wang, Li Xu, and Liang Lin*, “Local- and Holistic-structure Preserving Image Super Resolution via Deep Joint Component Learning”, Proc. of IEEE Conference on Multimedia and Expo (ICME), 2016. (Oral Presentation) [PDF]

  126. Liang Lin, Guangrun Wang, Rui Zhang, Ruimao Zhang, Xiaodan Liang, and Wangmeng Zuo, “Deep Structured Scene Parsing by Learning with Image Descriptions”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (Oral Presentation) [PDF][Dataset]

  127. Xiaodan Liang, Xiaohui Shen, Donglai Xiang, Jiashi Feng, Liang Lin*, and Shuicheng Yan, “Semantic Object Parsing with Local-Global Long Short-Term Memory”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [PDF]

  128. Keze Wang, Liang Lin*, Wangmeng Zuo, Shuhang Gu, and Lei Zhang, “Dictionary Pair Classifier Driven Convolutional Neural Networks for Object Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [PDF]

  129. Faqiang Wang, Wangmeng Zuo, Liang Lin, David Zhang, and Lei Zhang, “Joint Learning of Single-image and Cross-image Representations for Person Re-identification”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [PDF]

  130. Xiaodan Liang, Yunchao Wei, Xiaohui Shen, Zequn Jie, Jiashi Feng, Liang Lin*, and Shuicheng Yan, “Reversible Recursive Instance-level Object Segmentation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [PDF]

  131. Guangrun Wang, Liang Lin*, Shengyong Ding, Ya Li, and Qing Wang, “DARI: Distance metric And Representation Integration for Person Verification”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2016. [PDF]

  132. Shuye Zhang, Mude Lin, Tianshui Chen, Lianwen Jin, Liang Lin, “Character Proposal Network for Robust Text Extraction”, Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016. [PDF]

  133. Xiaodan Liang, Chunyan Xu, Xiaohui Shen, Jianchao Yang, Si Liu, Jinhui Tang, Liang Lin*, and Shuicheng Yan, “Human Parsing with Contextualized Convolutional Neural Network”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2015. (Oral Presentation) [PDF]

  134. Xiaodan Liang, Si Liu, Yunchao Wei, Luoqi Liu, Liang Lin, and Shuicheng Yan, “Towards Computational Baby Learning: A Weakly-supervised Approach for Object Detection”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2015. [PDF]

  135. Chenglong Li, Liang Lin*, Wangmeng Zuo, Shuicheng Yan, and Jin Tang, “SOLD: Sub-Optimal Low-Rank Decomposition for Efficient Video Segmentation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [PDF][Supp.]

  136. Wangmeng Zuo, Dongwei Ren, Shuhang Gu, Liang Lin, and Lei Zhang, “Discriminative Learning of Iteration-Wise Priors for Blind Deconvolution”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [PDF][Supp.]

  137. Si Liu, Xiaodan Liang, Luoqi Liu, Xiaohui Shen, Jianchao Yang, Changsheng Xu, Liang Lin, Xiaochun Cao, and Shuicheng Yan, “Matching-CNN Meets KNN: Quasi-Parametric Human Parsing”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [PDF]

  138. Liliang Zhang, Liang Lin*, Xian Wu, Shengyong Ding, and Lei Zhang, “End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning”, Proc. of ACM International Conference on Multimedia Retrieval (ACM ICMR), 2015. [PDF]

  139. Xiaolong Wang, Liliang Zhang, Liang Lin*, Zhujin Liang, and Wangmeng Zuo, “Deep Joint Task Learning for Generic Object Extraction”, Proc. of Advances in Neural Information Processing Systems (NIPS), 2014. [PDF]

  140. Keze Wang, Xiaolong Wang, Liang Lin*, Meng Wang, and Wangmeng Zuo, “3D Activity Recognition with Reconfigurable Convolutional Neural Networks”, Proc. of ACM International Conference on Multimedia (ACM MM), (full paper, Oral Presentation), 2014. [PDF]

  141. Si Liu, Xiaodan Liang, Luoqi Liu, Ke Lv, Liang Lin, and Shuicheng Yan, “Fashion Parsing with Video Context”, Proc. of ACM International Conference on Multimedia (ACM MM), (full paper, Oral Presentation), 2014. [PDF]

  142. Yuanlu Xu, Bingpeng Ma, Rui Huang, and Liang Lin, “Person Search in a Scene by Jointly Modeling People Commonness and Person Uniqueness”, Proc. of ACM International Conference on Multimedia (ACM MM), 2014. [PDF]

  143. Zhujin Liang, Xiaolong Wang, Rui Huang, and Liang Lin*, “An Expressive Deep Model for Parsing Human Action from a Single Image”, Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2014. (Best Student Paper Award) [PDF]

  144. Wei Yang, Ping Luo, and Liang Lin*, “Clothing Co-Parsing by Joint Image Segmentation and Labeling”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. [PDF]

  145. Xiaodan Liang, Qingxing Cao, Rui Huang, and Liang Lin, “Recognizing Focal Liver Lesions in Contrast-Enhanced Ultrasound with Discriminatively Trained Spatio-Temporal Model”, IEEE International Symposium on Biomedical Imaging (ISBI), 2014. [PDF]

  146. Xiaochun Cao, Hua Zhang, Si Liu, Xiaojie Guo, and Liang Lin, “SYM-FISH: A Symmetry-aware Flip Invariant Sketch Histogram Shape Descriptor”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2013. [PDF]

  147. Canyi Lu, Jinhui Tang, Min Lin, Liang Lin, Shuicheng Yan, and Zhouchen Lin, “Correntropy Induced L2 Graph for Robust Subspace Clustering”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2013. [PDF]

  148. Yuanlu Xu, Liang Lin*, Wei-Shi Zheng, and Xiaobai Liu, “Human Re-identification by Matching Compositional Template with Cluster Sampling”, Proc. of IEEE International Conference on Computer Vision (ICCV), 2013. [PDF]

  149. Xiaodan Liang, Liang Lin*, and Liangliang Cao, “Learning Latent Spatio-Temporal Compositional Model for Human Action Recognition”, Proc. ACM International Conference on Multimedia (ACM MM), (full paper, Oral Presentation), 2013. [PDF]

  150. Bingbing Ni, Yong Pei, Zhujin Liang, Liang Lin, and Pierre Moulin, “Integrating Multi-Stage Depth-Induced Contextual Information For Human Action Recognition and Localization”, Proc. of IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 2013. [PDF]

  151. Xiaolong Wang, Liang Lin*, Lichao Huang, and Shuicheng Yan, “Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. [PDF]

  152. Keyang Shi, Keze Wang, Jiangbo Lu, and Liang Lin*, “PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. [PDF]

  153. Xiaobai Liu, Liang Lin, and Alan L. Yuille, “Robust Region Grouping via Internal Patch Statistics”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013. [PDF]

  154. Xiaolong Wang, and Liang Lin*, “Dynamical And-Or Graph Learning for Object Shape Modeling and Detection”, Proc. of Advances in Neural Information Processing Systems (NIPS), 2012. [PDF]

  155. Tao Lin, Liang Lin*, and Qing Wang, “Robust Stroke-based Video Animation via Layered Motion and Correspondence”, Proc. of ACM International Conference on Multimedia (ACM MM), 2012. [PDF]

  156. Ping Luo, Xiaogang Wang, Liang Lin, and Xiaoou Tang, “Joint Semantic Segmentation by Searching for Compatible-Competitive References”, Proc. of ACM International Conference on Multimedia (ACM MM), 2012. [PDF]

  157. Liang Lin, Xiaolong Wang, Wei Yang, and Jian-Huang Lai, “Learning Contour-Fragment-based Shape Model with And-Or Tree Representation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. [PDF]

  158. Jiangbo Lu, Keyang Shi, Dongbo Min, Liang Lin, and Minh Do, “Cross-based Local Multipoint Filtering”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. [PDF]

  159. Xiaobai Liu, Jiashi Feng, Shuicheng Yan, Liang Lin, and Hai Jin, “Segment an Image by Looking into an Image Corpus”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [PDF]

  160. Ping Luo, Liang Lin*, and Hongyang Chao, “Learning Shape Detector by Quantizing Curve Segments with Multiple Distance Metrics”, Proc. of European Conference on Computer Vision (ECCV), 2010. [PDF]

  161. Liang Lin, Kun Zeng, Han Lv, Yizhou Wang, YingQing Xu, and Song-Chun Zhu, “Painterly Animation Using Video Semantics and Feature Correspondence”, Proc. of International Symposium on Non-Photorealistic Animation and Rendering (NPAR), 2010. (Runner-up Best Paper Award) [PDF] [Demo01] [Demo02] [Demo03] [Demo04] [Demo05]

  162. Yi Xie, Liang Lin*, and Yunde Jia, “Tracking Objects with Adaptive Feature Patches for PTZ Camera Visual Surveillance”, Proc. of IEEE International Conference on Pattern Recognition (ICPR), 2010. [PDF]

  163. Liang Lin, Kun Zeng, Xiaobai Liu, and Song-Chun Zhu, “Layered Graph Matching by Composite Cluster Sampling with Collaborative and Competitive Interactions”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009. [PDF]

  164. Xiaobai Liu, Liang Lin, Hai Jin, and Song-Chun Zhu, “Trajectory Parsing by Cluster Sampling in Spatio-temporal Graph”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009. [PDF]

  165. Liang Lin, Shaowu Peng, Jake Porway, Song-Chun Zhu, and Yongtian Wang, “An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples”, Proc. of IEEE International Conference on Computer Vision (ICCV), vol. 1: 419-426, 2007. [PDF]

  166. Liang Lin, Song-Chun Zhu, and Yongtian Wang, “Layered Graph Match with Graph Editing”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1: 885-892, 2007. [PDF]