9 papers
Visual Distortion Detection in UGC Images Using Large Multimodal Models
Ziheng Jia, Yingji Liang, Jiaying Qian +1
The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approaches based on large multimodal…
RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement
Ziheng Jia, Jiaying Qian, Zicheng Zhang +3
AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation model…
DyCoRM: Dynamic Criterion-Aware Reward Modeling for Text-to-Image Generation
Jiaying Qian, Ziheng Jia, Qian Zhang +5
With the continued advancement of text-to-image (T2I) generation, producing high-quality images is becoming increasingly attainable; consequently, user demands are shifting toward…
VITAL: Vision-Encoder-centered Pre-training for LMMs in Visual Quality Assessment
Ziheng Jia, Linhan Cao, Jinliang Han +6
Developing a robust visual quality assessment (VQualA) large multi-modal model (LMM) requires achieving versatility, powerfulness, and transferability. However, existing VQualA LMM…
Refine-IQA: Multi-Stage Reinforcement Finetuning for Perceptual Image Quality Assessment
Ziheng Jia, Jiaying Qian, Zicheng Zhang +2
Reinforcement fine-tuning (RFT) is a proliferating paradigm for LMM training. Analogous to high-level reasoning tasks, RFT is similarly applicable to low-level vision domains, incl…
DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models
Jiarui Wang, Huiyu Duan, Juntong Wang +8
With the rapid advancement of generative models, the realism of AI-generated images has significantly improved, posing critical challenges for verifying digital content authenticit…