5 papers
TranX-Adapter: Bridging Artifacts and Semantics within MLLMs for Robust AI-generated Image Detection
Wenbin Wang, Yuge Huang, Jianqing Xu +5
Rapid advances in AI-generated image (AIGI) technology enable highly realistic synthesis, threatening public information integrity and security. Recent studies have demonstrated th…
Thinking with Deltas: Incentivizing Reinforcement Learning via Differential Visual Reasoning Policy
Shujian Gao, Yuan Wang, Jiangtao Yan +2
Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced reasoning capabilities in Large Language Models. However, adapting RLVR to multimodal domains suffe…
PointAD+: Learning Hierarchical Representations for Zero-shot 3D Anomaly Detection
Qihang Zhou, Shibo He, Jiangtao Yan +2
In this paper, we aim to transfer CLIP's robust 2D generalization capabilities to identify 3D anomalies across unseen objects of highly diverse class semantics. To this end, we pro…
AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection
Bin-Bin Gao, Yue Zhou, Jiangtao Yan +7
Universal visual anomaly detection aims to identify anomalies from novel or unseen vision domains without additional fine-tuning, which is critical in open scenarios. Recent studie…
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection
Qihang Zhou, Jiangtao Yan, Shibo He +2
Zero-shot (ZS) 3D anomaly detection is a crucial yet unexplored field that addresses scenarios where target 3D training samples are unavailable due to practical concerns like priva…