4 papers
Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking
Wen Wen, Tianwu Zhi, Kanglong Fan +6
Improving vision-language models (VLMs) in the post-training stage typically relies on supervised fine-tuning or reinforcement learning, methods that necessitate costly, human-anno…
IQA-Spider: Unifying Multi-Granularity Image Quality Assessment with Reasoning, Grounding and Referring
Xinge Peng, Yiting Lu, Xin Li +1
We present IQA-Spider, the first image quality assessment (IQA) framework that unifies reasoning, grounding, and referring into a single LMM-based framework for multi-granularity q…
4DWorldBench: A Comprehensive Evaluation Framework for 3D/4D World Generation Models
Yiting Lu, Wei Luo, Peiyan Tu +8
World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct rea…
OmniQuality-R: Advancing Reward Models Through All-Encompassing Quality Assessment
Yiting Lu, Fengbin Guan, Yixin Gao +8
Current visual evaluation approaches are typically constrained to a single task. To address this, we propose OmniQuality-R, a unified reward modeling framework that transforms mult…