activity
20172022
most citedAttribute Recognition by Joint Recurrent Learning of Context and Correlation

36 citations · 60 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV20214 cited

Online Multiple Object Tracking with Cross-Task Synergy

Song Guo, Jingya Wang, Xinchao Wang +1

Modern online multiple object tracking (MOT) methods usually focus on two directions to improve tracking performance. One is to predict new positions in an incoming frame based on…

cs.CV20202 cited

Symbiotic Adversarial Learning for Attribute-based Person Search

Yu-Tong Cao, Jingya Wang, Dacheng Tao

Attribute-based person search is in significant demand for applications where no detected query images are available, such as identifying a criminal from witness. However, the task…

cs.CV2020

Pose-guided Visible Part Matching for Occluded Person ReID

Shang Gao, Jingya Wang, Huchuan Lu +1

Occluded person re-identification is a challenging task as the appearance varies substantially with various obstacles, especially in the crowd scenario. To address this issue, we p…

cs.CV2018

Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification

Jingya Wang, Xiatian Zhu, Shaogang Gong +1

Most existing person re-identification (re-id) methods require supervised model learning from a separate large set of pairwise labelled training data for every single camera pair.…

cs.CV201736 cited

Attribute Recognition by Joint Recurrent Learning of Context and Correlation

Jingya Wang, Xiatian Zhu, Shaogang Gong +1

Recognising semantic pedestrian attributes in surveillance images is a challenging task for computer vision, particularly when the imaging quality is poor with complex background c…

cs.CV2017

Discovering Visual Concept Structure with Sparse and Incomplete Tags

Jingya Wang, Xiatian Zhu, Shaogang Gong

Discovering automatically the semantic structure of tagged visual data (e.g. web videos and images) is important for visual data analysis and interpretation, enabling the machine i…