7 papers
PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing
Chengyu Fang, Chunming He, Yuelin Zhang +6
Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze distribution, spatially varying colo…
Controllable Video Generation: A Survey
Yue Ma, Kunyu Feng, Zhongyuan Hu +19
With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video…
AnimeDL-2M: Million-Scale AI-Generated Anime Image Detection and Localization in Diffusion Era
Chenyang Zhu, Xing Zhang, Yuyang Sun +2
Recent advances in image generation, particularly diffusion models, have significantly lowered the barrier for creating sophisticated forgeries, making image manipulation detection…
Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well
Chengyu Fang, Chunming He, Longxiang Tang +6
Camouflaged Object Segmentation (COS) remains challenging because camouflaged objects exhibit only subtle visual differences from their backgrounds and single-modality RGB methods…
MultiBooth: Towards Generating All Your Concepts in an Image from Text
Chenyang Zhu, Kai Li, Yue Ma +2
This paper introduces MultiBooth, a novel and efficient technique for multi-concept customization in image generation from text. Despite the significant advancements in customized…
Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts
Chenyang Zhu, Bin Xiao, Lin Shi +2
The recent Segment Anything Model (SAM) represents a significant breakthrough in scaling segmentation models, delivering strong performance across various downstream applications i…