240 citations · 805 across the 94 of their papers we have counts for
23 papers · 1 filter
Adapter Shield: A Unified Framework with Built-in Authentication for Preventing Unauthorized Zero-Shot Image-to-Image Generation
Jun Jia, Hongyi Miao, Yingjie Zhou +8
With the rapid progress in diffusion models, image synthesis has advanced to the stage of zero-shot image-to-image generation, where high-fidelity replication of facial identities…
DLADiff: A Dual-Layer Defense Framework against Fine-Tuning and Zero-Shot Customization of Diffusion Models
Jun Jia, Hongyi Miao, Yingjie Zhou +8
With the rapid advancement of diffusion models, a variety of fine-tuning methods have been developed, enabling high-fidelity image generation with high similarity to the target con…
Evaluating Dataset Watermarking for Fine-tuning Traceability of Customized Diffusion Models: A Comprehensive Benchmark and Removal Approach
Xincheng Wang, Hanchi Sun, Wenjun Sun +8
Recent fine-tuning techniques for diffusion models enable them to reproduce specific image sets, such as particular faces or artistic styles, but also introduce copyright and secur…
Exploring Instruction Data Quality for Explainable Image Quality Assessment
Yunhao Li, Sijing Wu, Jun Jia +5
In recent years, with the rapid development of large multimodal models (LMMs), explainable image quality assessment (IQA) has attracted increasing attention, aiming to understand t…
XGC-AVis: Towards Audio-Visual Content Understanding with a Multi-Agent Collaborative System
Yuqin Cao, Xiongkuo Min, Yixuan Gao +4
In this paper, we propose XGC-AVis, a multi-agent framework that enhances the audio-video temporal alignment capabilities of multimodal large models (MLLMs) and improves the effici…
VQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results
Sizhuo Ma, Wei-Ting Chen, Qiang Gao +56
Face images play a crucial role in numerous applications; however, real-world conditions frequently introduce degradations such as noise, blur, and compression artifacts, affecting…
SafetyFlow: An Agent-Flow System for Automated LLM Safety Benchmarking
Xiangyang Zhu, Yuan Tian, Chunyi Li +3
The rapid proliferation of large language models (LLMs) has intensified the requirement for reliable safety evaluation to uncover model vulnerabilities. To this end, numerous LLM s…
Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QA
Kaiwei Zhang, Qi Jia, Zijian Chen +5
Large language models (LLMs), while increasingly used in domains requiring factual rigor, often display a troubling behavior: sycophancy, the tendency to align with user beliefs re…
Engagement Prediction of Short Videos with Large Multimodal Models
Wei Sun, Linhan Cao, Yuqin Cao +7
The rapid proliferation of user-generated content (UGC) on short-form video platforms has made video engagement prediction increasingly important for optimizing recommendation syst…
Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation
Wei Sun, Weixia Zhang, Linhan Cao +5
Face image quality assessment (FIQA) is essential for various face-related applications. Although FIQA has been extensively studied and achieved significant progress, the computati…
Audio-Assisted Face Video Restoration with Temporal and Identity Complementary Learning
Yuqin Cao, Yixuan Gao, Wei Sun +3
Face videos accompanied by audio have become integral to our daily lives, while they often suffer from complex degradations. Most face video restoration methods neglect the intrins…
VQAThinker: Exploring Generalizable and Explainable Video Quality Assessment via Reinforcement Learning
Linhan Cao, Wei Sun, Weixia Zhang +6
Video quality assessment (VQA) aims to objectively quantify perceptual quality degradation in alignment with human visual perception. Despite recent advances, existing VQA models s…
CompressedVQA-HDR: Generalized Full-reference and No-reference Quality Assessment Models for Compressed High Dynamic Range Videos
Wei Sun, Linhan Cao, Kang Fu +5
Video compression is a standard procedure applied to all videos to minimize storage and transmission demands while preserving visual quality as much as possible. Therefore, evaluat…
ICME 2025 Generalizable HDR and SDR Video Quality Measurement Grand Challenge
Yixu Chen, Bowen Chen, Hai Wei +16
This paper reports IEEE International Conference on Multimedia \& Expo (ICME) 2025 Grand Challenge on Generalizable HDR and SDR Video Quality Measurement. With the rapid developmen…
Just Noticeable Difference for Large Multimodal Models
Zijian Chen, Yuan Tian, Yuze Sun +5
Just noticeable difference (JND), the minimum change that the human visual system (HVS) can perceive, has been studied for decades. Although recent work has extended this line of r…
NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results
Xiaohong Liu, Xiongkuo Min, Qiang Hu +92
This paper reports on the NTIRE 2025 XGC Quality Assessment Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) a…
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment
Shuhao Han, Haotian Fan, Fangyuan Kong +112
This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…
Generalizable Video Quality Assessment via Weak-to-Strong Learning
Linhan Cao, Wei Sun, Xiangyang Zhu +6
Video quality assessment (VQA) seeks to predict the perceptual quality of a video in alignment with human visual perception, serving as a fundamental tool for quantifying quality d…
AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images
Yunhao Li, Sijing Wu, Wei Sun +6
The rapid development of text-to-image (T2I) generation approaches has attracted extensive interest in evaluating the quality of generated images, leading to the development of var…
EEmo-Bench: A Benchmark for Multi-modal Large Language Models on Image Evoked Emotion Assessment
Lancheng Gao, Ziheng Jia, Yunhao Zeng +5
The furnishing of multi-modal large language models (MLLMs) has led to the emergence of numerous benchmark studies, particularly those evaluating their perception and understanding…
FVQ: A Large-Scale Dataset and an LMM-based Method for Face Video Quality Assessment
Sijing Wu, Yunhao Li, Ziwen Xu +4
Face video quality assessment (FVQA) deserves to be explored in addition to general video quality assessment (VQA), as face videos are the primary content on social media platforms…
Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content
Zicheng Zhang, Tengchuan Kou, Shushi Wang +9
Evaluating text-to-vision content hinges on two crucial aspects: visual quality and alignment. While significant progress has been made in developing objective models to assess the…
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao +2
Many video-to-audio (VTA) methods have been proposed for dubbing silent AI-generated videos. An efficient quality assessment method for AI-generated audio-visual content (AGAV) is…