collaborators

10 papers

cs.CV2026

MotionAtlas: Detailed Region Captioning for Motion-Centric Videos

Weisong Liu, Haochen Wang, Kuan Gao +8

We propose MotionAtlas, a system for detailed captioning of motion-centric videos, comprising (1) a dedicated human-annotated benchmark, (2) a scalable, high-quality pipeline to co…

cs.CV2026

Semantic Generative Tuning for Unified Multimodal Models

Songsong Yu, Yuxin Chen, Ying Shan +1

Unified multimodal models (UMMs) strive to consolidate visual understanding and visual generation within a single architecture. However, prevailing training paradigms independently…

cs.CV2026

Watch, Remember, Reason: Human-View Video Understanding with MLLMs

Jiahao Meng, Yue Tan, Qi Xu +12

Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research moves from short clips to long, multimodal, and knowledge-intensive video…

cs.CV2026

Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation

Junjie Wang, Xinghua Lou, Jason Li +8

Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a single-pass generation paradigm…

cs.CV2026

Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs

Haochen Wang, Yuhao Wang, Tao Zhang +13

While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the dense world with complex scenes, requiring fine-grained analysis of i…

cs.CV2025

Visual Reasoning Tracer: Object-Level Grounded Reasoning Benchmark

Haobo Yuan, Yueyi Sun, Yanwei Li +7

Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved performance on tasks such as visual grounding and visual question answering. However, the re…