28 citations · 108 across the 31 of their papers we have counts for
8 papers · 1 filter
DiffusionInst: Diffusion Model for Instance Segmentation
Zhangxuan Gu, Haoxing Chen, Zhuoer Xu +3
Diffusion frameworks have achieved comparable performance with previous state-of-the-art image generation models. Researchers are curious about its variants in discriminative tasks…
Hierarchical Dynamic Image Harmonization
Haoxing Chen, Zhangxuan Gu, Yaohui Li +4
Image harmonization is a critical task in computer vision, which aims to adjust the foreground to make it compatible with the background. Recent works mainly focus on using global…
A2: Efficient Automated Attacker for Boosting Adversarial Training
Zhuoer Xu, Guanghui Zhu, Changhua Meng +5
Based on the significant improvement of model robustness by AT (Adversarial Training), various variants have been proposed to further boost the performance. Well-recognized methods…
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
Jintang Li, Zhouxin Yu, Zulun Zhu +6
Recent years have seen a surge in research on dynamic graph representation learning, which aims to model temporal graphs that are dynamic and evolving constantly over time. However…
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
Jintang Li, Ruofan Wu, Wangbin Sun +6
The last years have witnessed the emergence of a promising self-supervised learning strategy, referred to as masked autoencoding. However, there is a lack of theoretical understand…
GUARD: Graph Universal Adversarial Defense
Jintang Li, Jie Liao, Ruofan Wu +5
Graph convolutional networks (GCNs) have been shown to be vulnerable to small adversarial perturbations, which becomes a severe threat and largely limits their applications in secu…