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20212023
most citedSemantic-guided Pixel Sampling for Cloth-Changing Person Re-identification

100 citations · 139 across the 8 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021★ 2 cited

LiT: Zero-Shot Transfer with Locked-image text Tuning

Xiaohua Zhai, Xiao Wang, Basil Mustafa +4

This paper presents contrastive-tuning, a simple method employing contrastive training to align image and text models while still taking advantage of their pre-training. In our emp…

cs.CV2021★ 12 cited

Learn to Match: Automatic Matching Network Design for Visual Tracking

Zhipeng Zhang, Yihao Liu, Xiao Wang +2

Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants. Besides the remar…

cs.CV2021★ 20 cited

VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

Xiao Wang, Jianing Li, Lin Zhu +6

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lo…

cs.CV2021★ 100 cited

Semantic-guided Pixel Sampling for Cloth-Changing Person Re-identification

Xiujun Shu, Ge Li, Xiao Wang +2

Cloth-changing person re-identification (re-ID) is a new rising research topic that aims at retrieving pedestrians whose clothes are changed. This task is quite challenging and has…

cs.CV2021★ 2 cited

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking

Xiao Wang, Xiujun Shu, Shiliang Zhang +4

Many RGB-T trackers attempt to attain robust feature representation by utilizing an adaptive weighting scheme (or attention mechanism). Different from these works, we propose a new…

cs.CV2021★ 2 cited

Large-Scale Spatio-Temporal Person Re-identification: Algorithms and Benchmark

Xiujun Shu, Xiao Wang, Xianghao Zang +4

Person re-identification (re-ID) in the scenario with large spatial and temporal spans has not been fully explored. This is partially because that, existing benchmark datasets were…