14 citations · 22 across the 7 of their papers we have counts for
4 papers · 1 filter
Features Based Adaptive Augmentation for Graph Contrastive Learning
Adnan Ali, Jinlong Li
Self-Supervised learning aims to eliminate the need for expensive annotation in graph representation learning, where graph contrastive learning (GCL) is trained with the self-super…
Pik-Fix: Restoring and Colorizing Old Photos
Runsheng Xu, Zhengzhong Tu, Yuanqi Du +6
Restoring and inpainting the visual memories that are present, but often impaired, in old photos remains an intriguing but unsolved research topic. Decades-old photos often suffer…
Exploring High-Order Structure for Robust Graph Structure Learning
Guangqian Yang, Yibing Zhan, Jinlong Li +3
Recent studies show that Graph Neural Networks (GNNs) are vulnerable to adversarial attack, i.e., an imperceptible structure perturbation can fool GNNs to make wrong predictions. S…
ROMNet: Renovate the Old Memories
Runsheng Xu, Zhengzhong Tu, Yuanqi Du +5
Renovating the memories in old photos is an intriguing research topic in computer vision fields. These legacy images often suffer from severe and commingled degradations such as cr…