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cs.CV2024
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Fenfang Tao, Guo-Sen Xie, Fang Zhao +1
Few-shot anomaly detection (FSAD) aims to detect unseen anomaly regions with the guidance of very few normal support images from the same class. Existing FSAD methods usually find…
cs.CV2024
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
Meiqi Cao, Rui Yan, Xiangbo Shu +3
Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activiti…
cs.CV2024
GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition
Guangzhao Dai, Xiangbo Shu, Wenhao Wu +2
Vision-Language Models (VLMs), pre-trained on large-scale datasets, have shown impressive performance in various visual recognition tasks. This advancement paves the way for notabl…