3 papers
cs.CV2025
ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
Xincheng Yao, Yan Luo, Zefeng Qian +1
The current mainstream and state-of-the-art anomaly detection (AD) methods are substantially established on pretrained feature networks yielded by ImageNet pretraining. However, re…
cs.CV2025
ResAD++: Towards Class Agnostic Anomaly Detection via Residual Feature Learning
Xincheng Yao, Chao Shi, Muming Zhao +2
This paper explores the problem of class-agnostic anomaly detection (AD), where the objective is to train one class-agnostic AD model that can generalize to detect anomalies in div…
cs.CV2025
Beyond Label Semantics: Language-Guided Action Anatomy for Few-shot Action Recognition
Zefeng Qian, Xincheng Yao, Yifei Huang +3
Few-shot action recognition (FSAR) aims to classify human actions in videos with only a small number of labeled samples per category. The scarcity of training data has driven recen…