3 citations · 3 across the 5 of their papers we have counts for
6 papers
MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models
Xincheng Yao, Zefeng Qian, Chao Shi +2
In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventional single- and multi-class AD…
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…
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…
Joint Image-Instance Spatial-Temporal Attention for Few-shot Action Recognition
Zefeng Qian, Chongyang Zhang, Yifei Huang +2
Few-shot Action Recognition (FSAR) constitutes a crucial challenge in computer vision, entailing the recognition of actions from a limited set of examples. Recent approaches mainly…
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection
Xincheng Yao, Ruoqi Li, Zefeng Qian +2
Unified anomaly detection (AD) is one of the most challenges for anomaly detection, where one unified model is trained with normal samples from multiple classes with the objective…
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection
Xincheng Yao, Ruoqi Li, Zefeng Qian +2
Humans recognize anomalies through two aspects: larger patch-wise representation discrepancies and weaker patch-to-normal-patch correlations. However, the previous AD methods didn'…