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What Makes Synthetic Data Effective in Image Segmentation
Jinjin Zhang, Xiefan Guo, Yizhou Jin +2
Driven by rapid advances in large-scale generative models, synthetic data has emerged as a promising solution for visual understanding. While modern diffusion models achieve remark…
Reasoning-Driven Anomaly Detection and Localization with Image-Level Supervision
Yizhou Jin, Yuezhu Feng, Jinjin Zhang +3
Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning and perceptual abilities for anomaly detection. However, most approaches remain confined to…
Towards Training-free Anomaly Detection with Vision and Language Foundation Models
Jinjin Zhang, Guodong Wang, Yizhou Jin +1
Anomaly detection is valuable for real-world applications, such as industrial quality inspection. However, most approaches focus on detecting local structural anomalies while negle…
ONER: Online Experience Replay for Incremental Anomaly Detection
Yizhou Jin, Jiahui Zhu, Guodong Wang +5
Incremental anomaly detection aims to sequentially identify defects in industrial product lines but suffers from catastrophic forgetting, primarily due to knowledge overwriting dur…