activity
20172022
most citedABD-Net: Attentive but Diverse Person Re-Identification

64 citations · 89 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2022★ 10 cited

End-to-End 3D Hand Pose Estimation from Stereo Cameras

Yuncheng Li, Zehao Xue, Yingying Wang +3

This work proposes an end-to-end approach to estimate full 3D hand pose from stereo cameras. Most existing methods of estimating hand pose from stereo cameras apply stereo matching…

cs.CV2022★ 3 cited

E^2TAD: An Energy-Efficient Tracking-based Action Detector

Xin Hu, Zhenyu Wu, Hao-Yu Miao +8

Video action detection (spatio-temporal action localization) is usually the starting point for human-centric intelligent analysis of videos nowadays. It has high practical impacts…

cs.CV2021

Weakly-guided Self-supervised Pretraining for Temporal Activity Detection

Kumara Kahatapitiya, Zhou Ren, Haoxiang Li +3

Temporal Activity Detection aims to predict activity classes per frame, in contrast to video-level predictions in Activity Classification (i.e., Activity Recognition). Due to the e…

cs.CV2020★ 4 cited

SaccadeNet: A Fast and Accurate Object Detector

Shiyi Lan, Zhou Ren, Yi Wu +2

Object detection is an essential step towards holistic scene understanding. Most existing object detection algorithms attend to certain object areas once and then predict the objec…

cs.CV2019★ 1 cited

Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification

Ye Yuan, Wuyang Chen, Tianlong Chen +4

Many real-world applications, such as city-scale traffic monitoring and control, requires large-scale re-identification. However, previous ReID methods often failed to address two…

cs.CV2019★ 64 cited

ABD-Net: Attentive but Diverse Person Re-Identification

Tianlong Chen, Shaojin Ding, Jingyi Xie +5

Attention mechanism has been shown to be effective for person re-identification (Re-ID). However, the learned attentive feature embeddings which are often not naturally diverse nor…

cs.CV2017★ 7 cited

Deep Regionlets for Object Detection

Hongyu Xu, Xutao Lv, Xiaoyu Wang +3

In this paper, we propose a novel object detection framework named "Deep Regionlets" by establishing a bridge between deep neural networks and conventional detection schema for acc…