News （课题组最近的消息）

Target Transformed Regression for Accurate Tracking
Y. Cui, C. Jiang, L. Wang, G. Wu
Technical Report, 2021.
[ Paper ] [ Code ]
Transformer for anchor-free tracking with obtaining SOTA performance

Fully Convolutional Online Tracking
Y. Cui, C. Jiang, L. Wang, G. Wu
Technical Report, 2020.
[ Paper ] [ Code ]
Online learning of both classification and regression branch in a fully convolutional manner.

Learning Spatiotemporal Features via Video and Text Pair Discrimination
T. Li, L. Wang
Technical Report, 2020.
[ Paper ] [ Code ]
We propose a weakly supervised video representation learning framework from text information.

3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop
H. Zhang, Y. Tian, X. Zhou, W. Ouyang, Y. Liu, L. Wang, Z. Sun
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Code ] [ Project Page ]

MGSampler: An Explainable Sampling Strategy for Video Action Recognition
Y. Zhi, Z. Tong, L. Wang, G. Wu
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Code (soon) ]
A simple, general, and explainable video sampling method.

MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports Actions
Y. Li, L. Chen, R. He, Z. Wang, G. Wu, L. Wang
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Data ] [ Code ] [ Challenge ]
A high-quality and fine-grained action detection benchmark.

TAM: Temporal Adaptive Module for Video Recognition
Z. Liu, L. Wang, W. Wu, C. Qian, T. Lu
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Code ]
Temporal adaptive module of self attention + dynamic filtering for video recognition.

Relaxed Transformer Decoders for Direct Action Proposal Generation
J. Tan, J. Tang, L. Wang, G. Wu
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Code ]
Transformer for direct action proposal generation

Cross-Modal Pyramid Translation for RGB-D Scene Recognition
in International Journal of Computer Vision (IJCV), in IJCV, 2021.
[ Paper ] [ Code ]
Journal extension of TRecgNet with pyramid translation extension.

TDN: Temporal Difference Networks for Efficient Action Recognition
L. Wang, Z. Tong, B. Ji, G. Wu
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[ Paper ] [ Code ]
Temporal modeling with an explicit difference operation.

Boundary-Aware Cascade Networks for Temporal Action Segmentation
Z. Wang, Z. Gao, L. Wang, Z. Li, and G. Wu
in European Conference on Computer Vision (ECCV), 2020.
[ Paper ] [ Code ]
SOTA performance for action segmentation on three benchmarks.

Context-Aware RCNN: a Baseline for Action Detection in Videos
J. Wu, Z. Kuang, L. Wang, W. Zhang, G. Wu
in European Conference on Computer Vision (ECCV), 2020.
[ Paper ] [ Code ]
A simple baseline for action detection in videos.

Actions as Moving Points
Y. Li, Z. Wang, L. Wang, G. Wu
in European Conference on Computer Vision (ECCV), 2020.
[ Paper ] [ Code ]
MOC-detector is an anchor-free action tubelet detector, obtaining SOTA on JHMDB and UCF.

Dynamic Sampling Networks for Efficient Action Recognition in Videos
Y. Zheng, Z. Liu, T. Lu, L. Wang
in IEEE Transactions on Image Processing (TIP), 2020.
[ Paper ]
A dynamic version of TSN for efficient action recognition.

V4D: 4D Convolutional Neural Networks for Video-Level Representation Learning
S. Zhang, S. Guo, W. Huang, M. Scott, L. Wang
in International Conference on Learning Representations (ICLR), 2020.
[ Paper ] [ Code ]
V4D is an extension over TSN for video-level representation learning.

TEA: Temporal Excitation and Aggregation for Action Recognition
Y. Li, B. Ji, X. Shi, J. Zhang, B. Kang, L. Wang
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
[ Paper ] [ Code ]
We propose a lightweight temporal module for video recognition.

TEINet: Towards an Efficient Architecture for Video Recognition
Z. Liu, D. Luo, Y. Wang, L. Wang, Y. Tai, C. Wang, J. Li, F. Huang, T. Lu
in AAAI Conference on Artificial Intelligence (AAAI), 2020.
[ Paper ]
An efficient architecture for video recognition based on 2D CNN.

LIP: Local Importance-based Pooling
Z. Gao, L. Wang and G. Wu
in IEEE International Conference on Computer Vision (ICCV), 2019.
[ Paper ] [ Code ]
A general downsampling alternative to max or average pooling.

Learning Actor Relation Graphs for Group Activity Recognition
J. Wang, L. Wang, L. Wang, J. Guo and G. Wu
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[ Paper ] [ Code ]
Obtaining STOA performance on datasets of Volleyball and Collective Activity.

Translate-to-Recognize Networks for RGB-D Scene Recognition
D. Du, L. Wang, H. Wang, K. Zhao and G. Wu
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[ Paper ] [ Code ] [ Project Page ]
A new cross-modal transfer framework for RGB-D scene recognition.

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), 2018.
[ Paper ] [ Code ]
STOA performance for event recognition 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 (TIP), 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 ] [ Journal Version]
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%.

Better Exploiting OS-CNNs for Better Event Recognition in Images
L. Wang, Z. Wang, S. Guo, and Y. Qiao
ChaLearn Looking at People (LAP) workshop, ICCV, 2015.
[ Paper ] [ BibTex ] [ Presentation ] [ Project Page ]
Obtain 84.7% mAP and secure the 3rd place.

Object-Scene Convolutional Neural Networks for Event Recognition in Images
L. Wang, Z. Wang, W. Du, and Y. Qiao
ChaLearn Looking at People (LAP) workshop, CVPR, 2015.
[ Paper ] [ BibTex ] [ Presentation ] [ Project Page ]
Obtain 85.5% mAP and rank 1st on the track of cultural event recognition.