80 citations · 112 across the 11 of their papers we have counts for
16 papers · 1 filter
Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning
Yiyang Chen, Shanshan Zhao, Lunhao Duan +2
Diffusion-based models, widely used in text-to-image generation, have proven effective in 2D representation learning. Recently, this framework has been extended to 3D self-supervis…
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…
Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification
Pengfei Wang, Changxing Ding, Wentao Tan +3
Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims at adapting a model trained on a labeled source domain to an unlabeled target domain. State-of-the-art obje…