1

Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization
To solve unsupervised anomaly detection and localization, we propose a novel framework that learns dense and compact distribution from normal images with a coarse-to-fine alignment process.
Ye Zheng, Xiang Wang, Rui Deng, Tianpeng Bao, Rui Zhao, Liwei Wu
PDF
Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization
MST: Masked Self-Supervised Transformer for Visual Representation
We present a novel Masked Self-supervised Transformer, which can explicitly capture the local context of an image while preserving the global semantic information.
Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang
PDF
MST: Masked Self-Supervised Transformer for Visual Representation