Limin Wang (王利民)
Multimedia Computing Group
Department of Computer Science and Technology
Nanjing University
Office: CS Building 506
Email: lmwang.nju [at] gmail.com

About Me (CV)

I am a Professor at Department of Computer Science and Technology and also affiliated with State Key Laboratory for Novel Software Technology, Nanjing University.

Previously, I received the B.S. degree from Nanjing University in 2011, and the Ph.D. degree from The Chinese University of Hong Kong under the supervision of Prof. Xiaoou Tang in 2015. From 2015 to 2018, I was a Post-Doctoral Researcher with Prof. Luc Van Gool in the Computer Vision Laboratory (CVL) at ETH Zurich.

News

  • 2018-08-19: One paper is accepted by ECCV 2018 and one by T-PAMI.
  • 2018-04-01: I join Nanjing University as a faculty member at Department of Computer Science and Technology.
  • 2017-11-28: We released a recent work on video architecture design for spatiotemporal feature learning. [ arXiv ] [ Code ].
  • 2017-09-08: We have released the TSN models learned in the Kinetics dataset. These models could be transferred well to the existing datasets for action recognition and detection [ Link ].
  • 2017-09-01: One paper is accepted by ICCV 2017 and one by IJCV.
  • 2017-07-18: I am invited to give a talk at the Workshop on Frontiers of Video Technology-2017 [ Slide ].
  • 2017-03-28: I am co-organizing the CVPR2017 workshop and challenge on Visual Understanding by Learning from Web Data. For more details, please see the workshop page and challenge page.
  • 2017-02-28: Two papers are accepted by CVPR 2017.
  • 2016-12-20: We release the code and models for SR-CNN paper [ Code ].
  • 2016-10-05: We release the code and models for Places2 scene recognition challenge [ arXiv ] [ Code ].
  • 2016-08-03: Code and model of Temporal Segment Networks is released [ arXiv ] [ Code ].
  • 2016-07-15: One paper is accepted by ECCV 2016 and one by BMVC 2016.
  • 2016-06-16: Our team secures the 1st place for untrimmed video classification at ActivityNet Challenge 2016 [ Result ].
    Basically, our solution is based on our works of Temporal Segment Networks (TSN) and Trajectory-pooled Deep-convolutional Descriptors (TDD).
  • 2016-03-01: Two papers are accepted by CVPR 2016.
  • 2015-12-10: Our SIAT_MMLAB team secures the 2nd place for scene recognition at ILSVRC 2015 [ Result ].
  • 2015-09-30: We rank 3rd for cultural event recognition on ChaLearn Looking at People challenge, at ICCV 2015.
  • 2015-08-07: We release the Places205-VGGNet models [ Link ].
  • 2015-07-22: Code of Trajectory-Pooled Deep-onvolutional Descriptors (TDD) is released [ Link ].
  • 2015-07-15: Very deep two stream ConvNets are proposed for action recognition [ Link ].
  • 2015-03-15: We are the 1st winner of both tracks for action recognition and cultural event recognition, on ChaLearn Looking at People Challenge at CVPR 2015.

Recent Publications [ Full List ] [ Google Scholar ]

Appearance-and-Relation Networks for Video Classification
L. Wang, W. Li, W. Li, and L. Van Gool
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[ Paper ] [ Code ]
A new architecture for spatiotemporal feature learning.
Transferring Deep Object and Scene Representations for Event Recognition in Still Images
L. Wang, Z. Wang, Y. Qiao, and L. Van Gool
in International Journal of Computer Vision (IJCV), 2017.
[ Paper ] [ Code ]
State of the art performance for event recognition in images on ChaLearn LAP cultural event, WIDER datasets.
Temporal Action Detection with Structured Segment Networks
Y. Zhao, Y. Xiong, L. Wang, Z. Wu, X. Tang, and D. Lin
in IEEE International Conference on Computer Vision (ICCV), 2017.
[ Paper ] [ Code ]
A new framework for temporal action localization.
UntrimmedNets for Weakly Supervised Action Recognition and Detection
L. Wang, Y. Xiong, D. Lin, and L. Van Gool
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[ Paper ] [ BibTex ][ Code ]
An end-to-end architecture to learn from untrimmed videos.
Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos
J. Song, L. Wang, L. Van Gool, and O. Hilliges
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[ Paper ] [ BibTex ][ Project Page ]
End-to-end learning of FCNs and spatio-temporal relational models.
Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs
L. Wang, S. Guo, W. Huang, Y. Xiong, and Y. Qiao
in IEEE Transactions on Image Processing, 2017.
[ arXiv ] [ BibTex ] [ Code ]
Solution to Places2 and LSUN challenge.
Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition
Z. Wang, L. Wang, Y. Wang, B. Zhang, and Y. Qiao
in IEEE Transactions on Image Processing, 2017.
[ arXiv ] [ BibTex ] [ Code ]
A hybrid representation combing deep networks and Fisher vector.
Two-Stream SR-CNNs for Action Recognition in Videos
Y. Wang, J. Song, L. Wang, O. Hilliges, and L. Van Gool
in British Machine Vision Conference (BMVC), 2016.
[ Paper ] [ BibTex ] [ Code ]
Explicitly incorporating human and object cues for action recognition
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. Van Gool
in European Conference on Computer Vision (ECCV), 2016.
[ Paper ] [ BibTex ] [ Poster ] [ Code ]
Proposing a segmental architecture and obtaining the state-of-the-art performance on UCF101 and HMDB51
CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016
Y. Xiong, L. Wang, Z. Wang, B. Zhang, H. Song, W. Li, D. Lin, Y. Qiao, L. Van Gool, and X. Tang
ActivityNet Large Scale Activity Recognition Challenge, in conjuction with CVPR, 2016.
[ Paper ] [ BibTex ] [ Presentation ] [ Code ]
Winner of ActivityNet challenge for untrimmed video classification
Actionness Estimation Using Hybrid Fully Convolutional Networks
L. Wang, Y. Qiao, X. Tang, and L. Van Gool
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
[ Paper ] [ BibTex ] [ Poster ] [ Project Page ] [ Code ]
Estimating actionness maps and generating action proposals
Real-time Action Recognition with Enhanced Motion Vector CNNs
B. Zhang, L. Wang, Z. Wang, Y. Qiao, and H. Wang
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
[ Paper ] [ BibTex ] [ Poster ] [ Project Page ] [ Code ]
Proposing a real-time action recognition system with two-stream CNNs.
Action Recognition with Trajectory-Pooled Deep-Convolutional Descriptors
L. Wang, Y. Qiao, and X. Tang
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
[ Paper ] [ BibTex ] [ Extended Abstract ] [ Poster ] [ Project Page ] [ Code ]
State-of-the-art performance: HMDB51: 65.9%, UCF101: 91.5%.

Contests

  • ActivityNet Large Scale Activity Recognition Challenge, 2016: Untrimmed Video Classification, Rank: 1/24.
  • ImageNet Large Scale Visual Recognition Challenge, 2015: Scene Recognition, Rank: 2/25.
  • ChaLearn Looking at People Challenge, 2015, Rank: 1/6
  • THUMOS Action Recognition Challenge, 2015, Rank: 5/11.
  • ChaLearn Looking at People Challenge, 2014 , Rank: 1/6, 4/17.
  • THUMOS Action Recognition Challenge, 2014, Rank: 4/14, 2/3.
  • ChaLearn Multi-Modal Gesture Recognition Challenge, 2013 , Rank: 4/54.
  • THUMOS Action Recognition Challenge, 2013, Rank: 4/16.

Academic Service

Journal Reviewer

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Image Processing

IEEE Transactions on Multimedia

IEEE Transactions on Circuits and Systems for Video Technology

Pattern Recognition

Pattern Recognition Letter

Image and Vision Computing

Computer Vision and Image Understanding


Conference Reviewer

IEEE Conference on Computer Vision and Pattern Recognition, 2017

IEEE International Conference on Automatic Face and Gesture Recognition, 2017

European Conference on Computer Vision, 2016

Asian Conference on Computer Vision, 2016

International Conference on Pattern Recognition, 2016

Friends

Wen Li (ETH), Jie Song (ETH), Sheng Guo (Malong), Weilin Huang (Malong), Bowen Zhang (USC), Zhe Wang (UCI), Wei Li (Google), Yuanjun Xiong (Amazon), Xiaojiang Peng (SIAT), Zhuowei Cai (Google), Xingxing Wang (NTU)

Last Updated on 1st Apr., 2018

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