collaborators

5 papers

cs.CV2026

ExeWorldBench: Benchmarking Code-Based Executable 3D World Modeling

Xinge Peng, Zhen Fang, Ruibing Wang +8

Coding agents are increasingly evolving beyond reproducing what a world looks like toward constructing executable worlds that capture how a world works. This shift calls for execut…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…