8 papers
An Evolutionary Agentic Approach for Open-ended Image Quality Perception
Zhenchen Tang, Bo Peng, Zichuan Wang +4
Generative models are rapidly expanding image quality assessment (IQA) beyond traditional fidelity factors to emerging dimensions such as physical plausibility and text-rendering c…
Same Attention, Different Truths: Put Logit-Lens over Visual Attention to Detect and Mitigate LVLM Object Hallucination
Zichuan Wang, Songlin Yang, Bo Peng +4
Large Vision-Language Models (LVLMs) often suffer from object hallucination, generating objects that are absent from the image. Prior work largely attributes this to insufficient v…
Endogenous Reprompting: Self-Evolving Cognitive Alignment for Unified Multimodal Models
Zhenchen Tang, Songlin Yang, Zichuan Wang +4
Unified Multimodal Models (UMMs) exhibit strong understanding, yet this capability often fails to effectively guide generation. We identify this as a Cognitive Gap: the model lacks…
Revisiting MLLM Based Image Quality Assessment: Errors and Remedy
Zhenchen Tang, Songlin Yang, Bo Peng +2
The rapid progress of multi-modal large language models (MLLMs) has boosted the task of image quality assessment (IQA). However, a key challenge arises from the inherent mismatch b…
HandEval: Taking the First Step Towards Hand Quality Evaluation in Generated Images
Zichuan Wang, Bo Peng, Songlin Yang +2
Although recent text-to-image (T2I) models have significantly improved the overall visual quality of generated images, they still struggle in the generation of accurate details in…
DREAM: A Benchmark Study for Deepfake photoREalism AssessMent
Bo Peng, Zichuan Wang, Sheng Yu +3
Deep learning based face-swap videos, widely known as deepfakes, have drawn wide attention due to their threat to information credibility. Recent works mainly focus on the problem…
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…
CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIP
Zhenchen Tang, Zichuan Wang, Bo Peng +1
With the rapid development of generative technologies, AI-Generated Images (AIGIs) have been widely applied in various aspects of daily life. However, due to the immaturity of the…