most citedDeep Ranking Model by Large Adaptive Margin Learning for Person Re-identification

43 citations · 62 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2017

Deep Self-Paced Learning for Person Re-Identification

Sanping Zhou, Jinjun Wang, Deyu Meng +4

Person re-identification (Re-ID) usually suffers from noisy samples with background clutter and mutual occlusion, which makes it extremely difficult to distinguish different indivi…

cs.CV20176 cited

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

Shun Zhang, Jia-Bin Huang, Jongwoo Lim +4

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in sc…

cs.CV20172 cited

Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification

Sanping Zhou, Jinjun Wang, Rui Shi +3

Person re-identification (Re-ID) aims at matching images of the same person across disjoint camera views, which is a challenging problem in multimedia analysis, multimedia editing…

cs.CV201743 cited

Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification

Jiayun Wang, Sanping Zhou, Jinjun Wang +1

Person re-identification aims to match images of the same person across disjoint camera views, which is a challenging problem in video surveillance. The major challenge of this tas…

cs.CV201711 cited

Single Image Super Resolution - When Model Adaptation Matters

Yudong Liang, Radu Timofte, Jinjun Wang +2

In the recent years impressive advances were made for single image super-resolution. Deep learning is behind a big part of this success. Deep(er) architecture design and external p…