activity
20232026
most citedTemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

2 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2026

EgoReasoner: Learning Egocentric 4D Reasoning via Task-Adaptive Structured Thinking

Fangrui Zhu, Yunfeng Xi, Jianmo Ni +9

Egocentric video understanding is inherently complex due to the dynamic 4D nature of the environment, where camera motion and object displacements necessitate a continuous re-evalu…

cs.CV2025

"PhyWorldBench": A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

Jing Gu, Xian Liu, Yu Zeng +8

Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains…

cs.CV2025

Struct2D: A Perception-Guided Framework for Spatial Reasoning in MLLMs

Fangrui Zhu, Hanhui Wang, Yiming Xie +4

Unlocking spatial reasoning in Multimodal Large Language Models (MLLMs) is crucial for enabling intelligent interaction with 3D environments. While prior efforts often rely on expl…

cs.CV2024★ 2 cited

TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

Mu Cai, Reuben Tan, Jianrui Zhang +12

Understanding fine-grained temporal dynamics is crucial for multimodal video comprehension and generation. Due to the lack of fine-grained temporal annotations, existing video benc…

cs.CV2024★ 1 cited

Towards Flexible Visual Relationship Segmentation

Fangrui Zhu, Jianwei Yang, Huaizu Jiang

Visual relationship understanding has been studied separately in human-object interaction(HOI) detection, scene graph generation(SGG), and referring relationships(RR) tasks. Given…

cs.CV2023

Zero-shot Referring Expression Comprehension via Structural Similarity Between Images and Captions

Zeyu Han, Fangrui Zhu, Qianru Lao +1

Zero-shot referring expression comprehension aims at localizing bounding boxes in an image corresponding to provided textual prompts, which requires: (i) a fine-grained disentangle…