27 citations · 43 across the 8 of their papers we have counts for
10 papers
X-ReID: Multi-granularity Information Interaction for Video-Based Visible-Infrared Person Re-Identification
Chenyang Yu, Xuehu Liu, Pingping Zhang +1
Large-scale vision-language models (e.g., CLIP) have recently achieved remarkable performance in retrieval tasks, yet their potential for Video-based Visible-Infrared Person Re-Ide…
UniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
Xiaoqi Zhao, Youwei Pang, Chenyang Yu +5
Multi-modal image segmentation faces real-world deployment challenges from incomplete/corrupted modalities degrading performance. While existing methods address training-inference…
Power Battery Detection
Xiaoqi Zhao, Peiqian Cao, Chenyang Yu +10
Power batteries are essential components in electric vehicles, where internal structural defects can pose serious safety risks. We conduct a comprehensive study on a new task, powe…
Inspiring the Next Generation of Segment Anything Models: Comprehensively Evaluate SAM and SAM 2 with Diverse Prompts Towards Context-Dependent Concepts under Different Scenes
Xiaoqi Zhao, Youwei Pang, Shijie Chang +10
As large-scale foundation models trained on billions of image--mask pairs covering a vast diversity of scenes, objects, and contexts, SAM and its upgraded version, SAM~2, have sign…
Part Representation Learning with Teacher-Student Decoder for Occluded Person Re-identification
Shang Gao, Chenyang Yu, Pingping Zhang +1
Occluded person re-identification (ReID) is a very challenging task due to the occlusion disturbance and incomplete target information. Leveraging external cues such as human pose…
TF-CLIP: Learning Text-free CLIP for Video-based Person Re-Identification
Chenyang Yu, Xuehu Liu, Yingquan Wang +2
Large-scale language-image pre-trained models (e.g., CLIP) have shown superior performances on many cross-modal retrieval tasks. However, the problem of transferring the knowledge…
Deeply-Coupled Convolution-Transformer with Spatial-temporal Complementary Learning for Video-based Person Re-identification
Xuehu Liu, Chenyang Yu, Pingping Zhang +1
Advanced deep Convolutional Neural Networks (CNNs) have shown great success in video-based person Re-Identification (Re-ID). However, they usually focus on the most obvious regions…
Mind Your Clever Neighbours: Unsupervised Person Re-identification via Adaptive Clustering Relationship Modeling
Lianjie Jia, Chenyang Yu, Xiehao Ye +3
Unsupervised person re-identification (Re-ID) attracts increasing attention due to its potential to resolve the scalability problem of supervised Re-ID models. Most existing unsupe…
A Video Is Worth Three Views: Trigeminal Transformers for Video-based Person Re-identification
Xuehu Liu, Pingping Zhang, Chenyang Yu +3
Video-based person re-identification (Re-ID) aims to retrieve video sequences of the same person under non-overlapping cameras. Previous methods usually focus on limited views, suc…
Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification
Xuehu Liu, Pingping Zhang, Chenyang Yu +2
Video-based person re-identification (Re-ID) aims to automatically retrieve video sequences of the same person under non-overlapping cameras. To achieve this goal, it is the key to…