activity
20192022
most citedFastReID: A Pytorch Toolbox for General Instance Re-identification

123 citations · 139 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV202210 cited

Gait Recognition in the Wild with Dense 3D Representations and A Benchmark

Jinkai Zheng, Xinchen Liu, Wu Liu +3

Existing studies for gait recognition are dominated by 2D representations like the silhouette or skeleton of the human body in constrained scenes. However, humans live and walk in…

cs.CV2021

Explainable Person Re-Identification with Attribute-guided Metric Distillation

Xiaodong Chen, Xinchen Liu, Wu Liu +3

Despite the great progress of person re-identification (ReID) with the adoption of Convolutional Neural Networks, current ReID models are opaque and only outputs a scalar distance…

cs.CV20211 cited

TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition

Jinkai Zheng, Xinchen Liu, Chenggang Yan +4

Gait, i.e., the movement pattern of human limbs during locomotion, is a promising biometric for the identification of persons. Despite significant improvement in gait recognition w…

cs.CV2020123 cited

FastReID: A Pytorch Toolbox for General Instance Re-identification

Lingxiao He, Xingyu Liao, Wu Liu +3

General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identificatio…

cs.CV20194 cited

Multi-Granularity Reasoning for Social Relation Recognition from Images

Meng Zhang, Xinchen Liu, Wu Liu +3

Discovering social relations in images can make machines better interpret the behavior of human beings. However, automatically recognizing social relations in images is a challengi…

cs.CV20191 cited

PVSS: A Progressive Vehicle Search System for Video Surveillance Networks

Xinchen Liu, Wu Liu, Huadong Ma +1

This paper is focused on the task of searching for a specific vehicle that appeared in the surveillance networks. Existing methods usually assume the vehicle images are well croppe…