collaborators

9 papers

cs.CV2026

TraceVision: Trajectory-Aware Vision-Language Model for Human-Like Spatial Understanding

Fan Yang, Shurong Zheng, Hongyin Zhao +5

Recent Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities in image understanding and natural language generation. However, current approaches focus predominan…

cs.CV2026

GeM-VG: Towards Generalized Multi-image Visual Grounding with Multimodal Large Language Models

Shurong Zheng, Yousong Zhu, Hongyin Zhao +4

Multimodal Large Language Models (MLLMs) have demonstrated impressive progress in single-image grounding and general multi-image understanding. Recently, some methods begin to addr…

cs.CV2025

From Seeing to Predicting: A Vision-Language Framework for Trajectory Forecasting and Controlled Video Generation

Fan Yang, Zhiyang Chen, Yousong Zhu +2

Current video generation models produce physically inconsistent motion that violates real-world dynamics. We propose TrajVLM-Gen, a two-stage framework for physics-aware image-to-v…

cs.CV2025

FOCUS: Unified Vision-Language Modeling for Interactive Editing Driven by Referential Segmentation

Fan Yang, Yousong Zhu, Xin Li +6

Recent Large Vision Language Models (LVLMs) demonstrate promising capabilities in unifying visual understanding and generative modeling, enabling both accurate content understandin…

cs.CV2025

Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referring

Yufei Zhan, Shurong Zheng, Yousong Zhu +4

Large Vision Language Models have achieved fine-grained object perception, but the limitation of image resolution remains a significant obstacle to surpassing the performance of ta…

cs.CV2025

VFaith: Do Large Multimodal Models Really Reason on Seen Images Rather than Previous Memories?

Jiachen Yu, Yufei Zhan, Ziheng Wu +3

Recent extensive works have demonstrated that by introducing long CoT, the capabilities of MLLMs to solve complex problems can be effectively enhanced. However, the reasons for the…