Gairdao Community

林倞个人主页

GAIR DAO 2025-04-25

谷歌学术主页 github主页 Email：linlng@mail.sysu.edu.cn

职务：

国家杰出青年基金获得者，Fellow of IAPR/IET，曾任商汤科技首席研发总监/研究院执行院长。

研究方向：

多模态感知与理解

— 场景语义解析；跨模态因果推断；跨领域泛化理解

— 自监督学习及预训练大模型；强化学习；认知及常识推理

多模态内容生成及交互

— 精准可控的图像视频生成；3D场景生成及编辑；数字人及元宇宙

— 具身智能与交互学习；自主机器人

工作经历：

Postdoctorial Fellow, Dec. 2007~Dec. 2009, working with Prof. Song-Chun Zhu Center for Vision, Cognition, Learning, and Autonomy, UCLA, USA
Associate Professor, Dec. 2009~Dec. 2013 School of Software, Sun Yat-Sen University, China
Visiting Scholar, Nov. 2013~Sept. 2015 Department of Computing, The Hong Kong Polytechnic University, Hong Kong
Visiting Scholar, Dec. 2015~Dec. 2016 Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong
Full Professor, Jan. 2014~Present School of Data and Computer ScienceComputing, Sun Yat-Sen University, China

科研项目

VTON 360: High-Fidelity Virtual Try-On from Any Viewing Direction
DAGSM: Disentangled Avatar Generation with GS-enhanced Mesh
Boosting the Dual-Stream Architecture in Ultra-High Resolution Segmentation with Resolution-Biased Uncertainty Estimation
Cross-modal Causal Relation Alignment for Video Question Grounding
Reproducible Vision-Language Models Meet Concepts Out of Pre-Training
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation
OVER-NAV: Elevating Iterative Vision-and-Language Navigation with Open-Vocabulary Detection and StructurEd Representation Correctable Landmark Discovery via Large Models for Vision-Language Navigation

奖项：

UCLA International Student Scholarship, 2006.
Beijing Excellent Students Awards, 2007.
“Mashixiu” Fellowship, Beijing Univ. of Tech. (BIT), 2007.
Awardee, Hundred talents Program, Sun Yat-Sen University, 2009.
“Runner-up Best Paper Award”, ACM NPAR, 2010.
“Second Prize in Young Faculty Teaching Competition”, Sun Yat-Sen University, 2010.
“Zhuoyue-rencai Program”, Sun Yat-Sen University, 2011.
Nomination for National Excellent PhD Thesis Award, China, 2011.
Awardee, Program of Guangzhou Zhujiang Star of Science and Technology, Guangzhou, China, 2011.
“Google Faculty Award”, Google (China) Inc, 2012.
Awardee, Program of New Century Excellent Talents in University, Ministry of Education, China, 2012.
Awardee, Guangdong Natural Science Funds for Distinguished Young Scholars, 2013.
“Best Student Paper Award”, IEEE ICME 2014.
Hong Kong Scholars Award, The Society of Hong Kong Scholars, 2014.
Awardee, Program of Guangdong Top Young Innovative Talents, 2015.
Awardee, Excellent Young Scientists of NSFC, 2016.
“The World’s First 10K Best Paper Diamond Award”, IEEE ICME 2017.
Awardee, Program of National Ten Thousand Talents, China, 2017.
“CCF Qingzhu Award”, China Computer Federation, 2018.
“Annual Pattern Recognition Best Paper Award”, Pattern Recognition (Elsevier), 2018.

论文成果

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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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. [Code]
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. [Code]
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.
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. [Code]
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. [Code]
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.
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.
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. [Code]
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.
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.
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.
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.
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.
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.
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.
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.
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.
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. [Dataset]
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. [Code]
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.
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.
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.
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.
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.
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.
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.
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.
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. [Code]
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. [Code with Datasets]
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. [Code]
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. [Code]
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. [Code]
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.
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. [Code]
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. [Page with Code]
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. [Code]
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. [Code]
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. [Page with Data]
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.
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.
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.
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.
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.
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.
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. [Page with Code]
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]
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. [Supplemental Material] [Page with Code]
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.
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.
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.
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. [Code]
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.
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. [Page with Code]
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.
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.
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.
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.
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. [Page with Code]
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.
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. [Page with Code]
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.
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. [Page with Code]
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.
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. [Code]
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.
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. [Page with Data]
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. [Page with Code]
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. [Page with Code]
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.
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. [Page with Code]
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. [Page with Code]
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.
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.
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.
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.
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.
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.
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. (Best Paper Award)
Zhihua Chen, Wangmeng Zuo, Qinghua Hu, and Liang Lin, “Kernel Sparse Representation for Time Series Classification”, Information Sciences, 292(20): 15-26, 2015.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

媒体文章：

林倞教授详解具身智能未来趋势：人机物高效融合

商汤首席研发总监林倞：20张PPT谈四大领域产业布局｜2016 CAIIC

暗物智能CEO林倞：五层认知架构，重塑多模态人机互动产业化｜CCF-GAIR 2020

交流活动：

International Symposium on Non-Photorealistic Animation and Rendering, France, Jun, 2010 Topic: From Video Content Extraction to Painterly Animation
Advanced Digital Science Center, Singapore, Oct., 2011 Topic: Key Advances in Image and Video Parsing
School of Electrical and Computer Engineering at Carnegie Mellon University, U.S., Jun., 2012 Topic: Latent Structured Learning with Non-Convex Optimization
ACM International Conference on Multimedia, Spain, Oct., 2013 Topic: Learning Latent Spatio-Temporal Compositional Model for Human Action Recognition
Microsoft eScience Workshop 2013, Beijing, Oct., 2013 Topic: Distributed Learning Systems for Large-Scale Object Detection
VALSE: Vision And Learning Seminar, China, April, 2014 Topic: Inference and Learning with Grammar Models for Visual Recognition
IEEE International Conference on Multimedia and Expo, China, July, 2014 Topic: Sparse Representation Learning for Data Driven Parsing
ACM International Conference on Multimedia, U.S., Oct., 2014 Topic: Deep Structured Models for Human Activity Recognition
ACM Multimedia Tutorial (Half-Day), Australia, Oct., 2015 Topic: Human-centric Images and Videos Analysis
IEEE International Conference on Computer Vision, Chile, Dec., 2015 Topic: Contextualized Convolutional Neural Network for Human Parsing
Asian Conference on Machine Learning, Hong Kong, Nov., 2015 Topic: Deep Similarity Learning for Person Verification
IEEE Computer Vision and Pattern Recognition, United States, Jun., 2016 Topic: Deep Structured Scene Parsing by Learning with Image Descriptions
ACM Turing 50th Celebration Conference – China, May, 2017 Topic: Beyond Supervised Deep Learning for Visual Understanding

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