collaborators

17 papers

cs.CV2026

GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation

Yuhao Wan, Lijuan Liu, Jingzhi Zhou +6

Previous works that leverage video models for image-to-3D scene generation often suffer from geometric distortions and blurry content. Using video generation models to implicitly m…

cs.CV2026

Rethinking Token-Level Policy Optimization for Multimodal Chain-of-Thought

Yunheng Li, Hangyi Kuang, Hengrui Zhang +4

Multimodal Chain-of-Thought (CoT) reasoning requires large vision-language models to construct reasoning trajectories that interleave perceptual grounding with multi-step inference…

cs.CV2026

Towards Universal Video MLLMs with Attribute-Structured and Quality-Verified Instructions

Yunheng Li, Hengrui Zhang, Meng-Hao Guo +5

Universal video understanding requires modeling fine-grained visual and audio information over time in diverse real-world scenarios. However, the performance of existing models is…

cs.CV2025

Unbiased Region-Language Alignment for Open-Vocabulary Dense Prediction

Yunheng Li, Yuxuan Li, Quansheng Zeng +3

Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated impressive zero-shot recognition capability, but still underperform in dense prediction tasks. Self-disti…

cs.CV2025

SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection

Yuxuan Li, Xiang Li, Yunheng Li +5

With the rapid advancement of remote sensing technology, high-resolution multi-modal imagery is now more widely accessible. Conventional Object detection models are trained on a si…

cs.CV2025

TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs

Yunheng Li, Jing Cheng, Shaoyong Jia +4

This paper introduces TempSamp-R1, a new reinforcement fine-tuning framework designed to improve the effectiveness of adapting multimodal large language models (MLLMs) to video tem…