1 citations · 1 across the 5 of their papers we have counts for
5 papers
Enhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer
Xinyue Chen, Miaojing Shi, Zijian Zhou +2
Generalized few-shot semantic segmentation (GFSS) aims to segment objects of both base and novel classes, using sufficient samples of base classes and few samples of novel classes.…
HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Cloud Segmentation
Tianpei Zou, Sanqing Qu, Zhijun Li +4
3D point cloud segmentation has received significant interest for its growing applications. However, the generalization ability of models suffers in dynamic scenarios due to the di…
MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection
Boyang Peng, Sanqing Qu, Yong Wu +5
Deep learning has achieved remarkable progress in various applications, heightening the importance of safeguarding the intellectual property (IP) of well-trained models. It entails…
LEAD: Learning Decomposition for Source-free Universal Domain Adaptation
Sanqing Qu, Tianpei Zou, Lianghua He +4
Universal Domain Adaptation (UniDA) targets knowledge transfer in the presence of both covariate and label shifts. Recently, Source-free Universal Domain Adaptation (SF-UniDA) has…
Hierarchical Dynamic Masks for Visual Explanation of Neural Networks
Yitao Peng, Longzhen Yang, Yihang Liu +1
Saliency methods generating visual explanatory maps representing the importance of image pixels for model classification is a popular technique for explaining neural network decisi…