460 citations · 2k across the 40 of their papers we have counts for
11 papers · 1 filter
Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks
Jiehong Lin, Zewei Wei, Changxing Ding +1
It is difficult to precisely annotate object instances and their semantics in 3D space, and as such, synthetic data are extensively used for these tasks, e.g., category-level 6D ob…
Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
Zhiyin Shao, Xinyu Zhang, Meng Fang +3
Text-to-image person re-identification (ReID) aims to search for pedestrian images of an interested identity via textual descriptions. It is challenging due to both rich intra-moda…
Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection
Xubin Zhong, Changxing Ding, Zijian Li +1
Human-Object Interaction (HOI) detection is a core task for high-level image understanding. Recently, Detection Transformer (DETR)-based HOI detectors have become popular due to th…
1st Place Solution to the EPIC-Kitchens Action Anticipation Challenge 2022
Zeyu Jiang, Changxing Ding
In this report, we describe the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2022. In this competition, we develop the following two appro…
Context Sensing Attention Network for Video-based Person Re-identification
Kan Wang, Changxing Ding, Jianxin Pang +1
Video-based person re-identification (ReID) is challenging due to the presence of various interferences in video frames. Recent approaches handle this problem using temporal aggreg…
Style Interleaved Learning for Generalizable Person Re-identification
Wentao Tan, Changxing Ding, Pengfei Wang +2
Domain generalization (DG) for person re-identification (ReID) is a challenging problem, as access to target domain data is not permitted during the training process. Most existing…
HL-Net: Heterophily Learning Network for Scene Graph Generation
Xin Lin, Changxing Ding, Yibing Zhan +2
Scene graph generation (SGG) aims to detect objects and predict their pairwise relationships within an image. Current SGG methods typically utilize graph neural networks (GNNs) to…
RU-Net: Regularized Unrolling Network for Scene Graph Generation
Xin Lin, Changxing Ding, Jing Zhang +2
Scene graph generation (SGG) aims to detect objects and predict the relationships between each pair of objects. Existing SGG methods usually suffer from several issues, including 1…
Few-Shot Head Swapping in the Wild
Changyong Shu, Hemao Wu, Hang Zhou +7
The head swapping task aims at flawlessly placing a source head onto a target body, which is of great importance to various entertainment scenarios. While face swapping has drawn m…
MobileFaceSwap: A Lightweight Framework for Video Face Swapping
Zhiliang Xu, Zhibin Hong, Changxing Ding +4
Advanced face swapping methods have achieved appealing results. However, most of these methods have many parameters and computations, which makes it challenging to apply them in re…
Quality-aware Part Models for Occluded Person Re-identification
Pengfei Wang, Changxing Ding, Zhiyin Shao +3
Occlusion poses a major challenge for person re-identification (ReID). Existing approaches typically rely on outside tools to infer visible body parts, which may be suboptimal in t…