activity
20182021
most citedOnline Multi-Object Tracking with Dual Matching Attention Networks

3 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

MPASNET: Motion Prior-Aware Siamese Network for Unsupervised Deep Crowd Segmentation in Video Scenes

Jinhai Yang, Hua Yang

Crowd segmentation is a fundamental task serving as the basis of crowded scene analysis, and it is highly desirable to obtain refined pixel-level segmentation maps. However, it rem…

cs.CV20191 cited

Distribution Context Aware Loss for Person Re-identification

Zhigang Chang, Qin Zhou, Mingyang Yu +3

To learn the optimal similarity function between probe and gallery images in Person re-identification, effective deep metric learning methods have been extensively explored to obta…

cs.CV20193 cited

Online Multi-Object Tracking with Dual Matching Attention Networks

Ji Zhu, Hua Yang, Nian Liu +3

In this paper, we propose an online Multi-Object Tracking (MOT) approach which integrates the merits of single object tracking and data association methods in a unified framework t…

cs.CV2018

Robust and Efficient Graph Correspondence Transfer for Person Re-identification

Qin Zhou, Heng Fan, Hua Yang +4

Spatial misalignment caused by variations in poses and viewpoints is one of the most critical issues that hinders the performance improvement in existing person re-identification (…

cs.CV2018

Weighted Bilinear Coding over Salient Body Parts for Person Re-identification

Zhigang Chang, Qin Zhou, Heng Fan +4

Deep convolutional neural networks (CNNs) have demonstrated dominant performance in person re-identification (Re-ID). Existing CNN based methods utilize global average pooling (GAP…