18 papers · 1 filter
GAP-SAM: A Global Artifact Prior for Generalizable AI-Generated Image Manipulation Localization
Haozhen Yan, Siyuan Shan, Zijian Yu +4
AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel supervision entangles forensic…
Enhancing Localized Reasoning for Long Video Understanding via Efficient Segment-to-Video Supervision
Beibei Zhang, Chao Xu, Jun Lan +4
Though Multimodal Large Language Models (MLLMs) have shown impressive potential in video understanding, long video understanding (LVU) remains challenging since distracting noise i…
Maintain Plasticity in Long-timescale Continual Test-time Adaptation
Yanshuo Wang, Xuesong Li, Jinguang Tong +5
Continual test-time domain adaptation (CTTA) aims to adjust pre-trained source models to perform well over time across non-stationary target environments. While previous methods ha…
COCO-Inpaint: A Benchmark for Detecting and Localizing Inpainting-Based Image Manipulations
Haozhen Yan, Yan Hong, Jiahui Zhan +5
Recent advances in image manipulation have enabled highly photorealistic content generation, but also lowered the barrier to arbitrary editing, raising concerns about multimedia au…
Locate-Then-Examine: Grounded Region Reasoning Improves Detection of AI-Generated Images
Yikun Ji, Yan Hong, Bowen Deng +5
The rapid growth of AI-generated imagery has blurred the boundary between real and synthetic content, raising practical concerns for digital integrity. Vision-language models (VLMs…
Adaptive and Balanced Re-initialization for Long-timescale Continual Test-time Domain Adaptation
Yanshuo Wang, Jinguang Tong, Jun Lan +5
Continual test-time domain adaptation (CTTA) aims to adjust models so that they can perform well over time across non-stationary environments. While previous methods have made cons…