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Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis
Shanshan Zhao, Mingming Gong, Xi Li +1
Recent years have witnessed the great success of deep learning on various point cloud analysis tasks, e.g., classification and semantic segmentation. Since point cloud data is spar…
Variational Distillation for Multi-View Learning
Xudong Tian, Zhizhong Zhang, Cong Wang +6
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions. Howev…
Visual Superordinate Abstraction for Robust Concept Learning
Qi Zheng, Chaoyue Wang, Dadong Wang +1
Concept learning constructs visual representations that are connected to linguistic semantics, which is fundamental to vision-language tasks. Although promising progress has been m…
Neural Maximum A Posteriori Estimation on Unpaired Data for Motion Deblurring
Youjian Zhang, Chaoyue Wang, Dacheng Tao
Real-world dynamic scene deblurring has long been a challenging task since paired blurry-sharp training data is unavailable. Conventional Maximum A Posteriori estimation and deep l…
Source-Free Domain Adaptation via Distribution Estimation
Ning Ding, Yixing Xu, Yehui Tang +3
Domain Adaptation aims to transfer the knowledge learned from a labeled source domain to an unlabeled target domain whose data distributions are different. However, the training da…
Defensive Patches for Robust Recognition in the Physical World
Jiakai Wang, Zixin Yin, Pengfei Hu +5
To operate in real-world high-stakes environments, deep learning systems have to endure noises that have been continuously thwarting their robustness. Data-end defense, which impro…