5 citations · 11 across the 25 of their papers we have counts for
14 papers · 1 filter
Omni-Referring Image Segmentation
Qiancheng Zheng, Yunhang Shen, Gen Luo +5
In this paper, we propose a novel task termed Omni-Referring Image Segmentation (OmniRIS) towards highly generalized image segmentation. Compared with existing unimodally condition…
M4-BLIP: Advancing Multi-Modal Media Manipulation Detection through Face-Enhanced Local Analysis
Hang Wu, Ke Sun, Jiayi Ji +2
In the contemporary digital landscape, multi-modal media manipulation has emerged as a significant societal threat, impacting the reliability and integrity of information dissemina…
CIR-CoT: Towards Interpretable Composed Image Retrieval via End-to-End Chain-of-Thought Reasoning
Weihuang Lin, Yiwei Ma, Jiayi Ji +2
Composed Image Retrieval (CIR), which aims to find a target image from a reference image and a modification text, presents the core challenge of performing unified reasoning across…
HRSeg: High-Resolution Visual Perception and Enhancement for Reasoning Segmentation
Weihuang Lin, Yiwei Ma, Xiaoshuai Sun +4
The reasoning segmentation task involves segmenting objects within an image by interpreting implicit user instructions, which may encompass subtleties such as contextual cues and o…
MIHBench: Benchmarking and Mitigating Multi-Image Hallucinations in Multimodal Large Language Models
Jiale Li, Mingrui Wu, Zixiang Jin +5
Despite growing interest in hallucination in Multimodal Large Language Models, existing studies primarily focus on single-image settings, leaving hallucination in multi-image scena…
AIGI-Holmes: Towards Explainable and Generalizable AI-Generated Image Detection via Multimodal Large Language Models
Ziyin Zhou, Yunpeng Luo, Yuanchen Wu +7
The rapid development of AI-generated content (AIGC) technology has led to the misuse of highly realistic AI-generated images (AIGI) in spreading misinformation, posing a threat to…
RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning
Mingrui Wu, Lu Wang, Pu Zhao +14
Despite recent progress in text-to-image (T2I) generation, existing models often struggle to faithfully capture user intentions from short and under-specified prompts. While prior…
An Efficient and Mixed Heterogeneous Model for Image Restoration
Yubin Gu, Yuan Meng, Kaihang Zheng +5
Image restoration~(IR), as a fundamental multimedia data processing task, has a significant impact on downstream visual applications. In recent years, researchers have focused on d…
Zooming In on Fakes: A Novel Dataset for Localized AI-Generated Image Detection with Forgery Amplification Approach
Lvpan Cai, Haowei Wang, Jiayi Ji +4
The rise of AI-generated image tools has made localized forgeries increasingly realistic, posing challenges for visual content integrity. Although recent efforts have explored loca…
Exploring the Collaborative Advantage of Low-level Information on Generalizable AI-Generated Image Detection
Ziyin Zhou, Ke Sun, Zhongxi Chen +5
Existing state-of-the-art AI-Generated image detection methods mostly consider extracting low-level information from RGB images to help improve the generalization of AI-Generated i…
MLLM-Selector: Necessity and Diversity-driven High-Value Data Selection for Enhanced Visual Instruction Tuning
Yiwei Ma, Guohai Xu, Xiaoshuai Sun +4
Visual instruction tuning (VIT) has emerged as a crucial technique for enabling multi-modal large language models (MLLMs) to follow user instructions adeptly. Yet, a significant ga…
Grounded Chain-of-Thought for Multimodal Large Language Models
Qiong Wu, Xiangcong Yang, Yiyi Zhou +4
Despite great progress, existing multimodal large language models (MLLMs) are prone to visual hallucination, greatly impeding their trustworthy applications. In this paper, we stud…
AdaFlow: Efficient Long Video Editing via Adaptive Attention Slimming And Keyframe Selection
Shuheng Zhang, Yuqi Liu, Hongbo Zhou +4
Despite great progress, text-driven long video editing is still notoriously challenging mainly due to excessive memory overhead. Although recent efforts have simplified this task i…
IPDN: Image-enhanced Prompt Decoding Network for 3D Referring Expression Segmentation
Qi Chen, Changli Wu, Jiayi Ji +3
3D Referring Expression Segmentation (3D-RES) aims to segment point cloud scenes based on a given expression. However, existing 3D-RES approaches face two major challenges: feature…