4 papers
RAID: Retrieval-Augmented Anomaly Detection
Mingxiu Cai, Zhe Zhang, Gaochang Wu +2
Unsupervised Anomaly Detection (UAD) aims to identify abnormal regions by establishing correspondences between test images and normal templates. Existing methods primarily rely on…
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Hanxiao Wang +3
Unsupervised anomaly detection (UAD) seeks to localize the anomaly mask of an input image with respect to normal samples. Either by reconstructing normal counterparts (reconstructi…
Unified Domain Adaptive Semantic Segmentation
Zhe Zhang, Gaochang Wu, Jing Zhang +3
Unsupervised Domain Adaptive Semantic Segmentation (UDA-SS) aims to transfer the supervision from a labeled source domain to an unlabeled target domain. The majority of existing UD…
Geo-NI: Geometry-aware Neural Interpolation for Light Field Rendering
Gaochang Wu, Yuemei Zhou, Yebin Liu +2
In this paper, we present a Geometry-aware Neural Interpolation (Geo-NI) framework for light field rendering. Previous learning-based approaches either rely on the capability of ne…