123 citations · 463 across the 13 of their papers we have counts for
13 papers · 1 filter
Learning Feature Recovery Transformer for Occluded Person Re-identification
Boqiang Xu, Lingxiao He, Jian Liang +1
One major issue that challenges person re-identification (Re-ID) is the ubiquitous occlusion over the captured persons. There are two main challenges for the occluded person Re-ID…
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…
Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification
Boqiang Xu, Jian Liang, Lingxiao He +1
Domain generalizable (DG) person re-identification (ReID) aims to test across unseen domains without access to the target domain data at training time, which is a realistic but cha…
Semi-Supervised Domain Generalizable Person Re-Identification
Lingxiao He, Wu Liu, Jian Liang +4
Existing person re-identification (re-id) methods are stuck when deployed to a new unseen scenario despite the success in cross-camera person matching. Recent efforts have been sub…
Learning Instance-level Spatial-Temporal Patterns for Person Re-identification
Min Ren, Lingxiao He, Xingyu Liao +3
Person re-identification (Re-ID) aims to match pedestrians under dis-joint cameras. Most Re-ID methods formulate it as visual representation learning and image search, and its accu…
Group-aware Label Transfer for Domain Adaptive Person Re-identification
Kecheng Zheng, Wu Liu, Lingxiao He +3
Unsupervised Domain Adaptive (UDA) person re-identification (ReID) aims at adapting the model trained on a labeled source-domain dataset to a target-domain dataset without any furt…
Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification
Boqiang Xu, Lingxiao He, Xingyu Liao +3
Person re-identification (Re-ID) aims at retrieving an input person image from a set of images captured by multiple cameras. Although recent Re-ID methods have made great success,…
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…
Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification
Lingxiao He, Yinggang Wang, Wu Liu +4
Re-identifying a person across multiple disjoint camera views is important for intelligent video surveillance, smart retailing and many other applications. However, existing person…
Recognizing Partial Biometric Patterns
Lingxiao He, Zhenan Sun, Yuhao Zhu +1
Biometric recognition on partial captured targets is challenging, where only several partial observations of objects are available for matching. In this area, deep learning based m…
SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification
Xing Fan, Hao Luo, Xuan Zhang +3
Holistic person re-identification (ReID) has received extensive study in the past few years and achieves impressive progress. However, persons are often occluded by obstacles or ot…
Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention
Xingyu Liao, Lingxiao He, Zhouwang Yang +1
Video-based person re-identification (ReID) is a challenging problem, where some video tracks of people across non-overlapping cameras are available for matching. Feature aggregati…
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free Approach
Lingxiao He, Jian Liang, Haiqing Li +1
Partial person re-identification (re-id) is a challenging problem, where only several partial observations (images) of people are available for matching. However, few studies have…