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20212026
most citedCan Action be Imitated? Learn to Reconstruct and Transfer Human Dynamics from Videos

3 citations · 4 across the 8 of their papers we have counts for

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cs.CV2026

The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering

Yuqian Fu, Tianwen Qian, Yanjun Li +30

EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize beyond common daily-life scena…

cs.CV2026

STABLE: Simulation-Ready Tabletop Layout Generation via a Semantics-Physics Dual System

Zhen Luo, Yixuan Yang, Xudong Xu +5

Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. However, existing task-to-scene ge…

cs.CV2026

EgoSound: Benchmarking Sound Understanding in Egocentric Videos

Bingwen Zhu, Yuqian Fu, Qiaole Dong +6

Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in vision-language understanding. Yet, human perception is inherently multisensory, integrating…

cs.CV2025

V-SAM: Marrying SAM2 with Multi-Prompt Experts for Cross-View Object Correspondence

Jiancheng Pan, Runze Wang, Tianwen Qian +7

Cross-view object correspondence, exemplified by the representative task of ego-exo object correspondence, aims to establish consistent associations of the same object across diffe…

cs.CV2025

Cross-View Multi-Modal Segmentation @ Ego-Exo4D Challenges 2025

Yuqian Fu, Runze Wang, Yanwei Fu +2

In this report, we present a cross-view multi-modal object segmentation approach for the object correspondence task in the Ego-Exo4D Correspondence Challenges 2025. Given object qu…

cs.CV2025

Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection

Yu Li, Xingyu Qiu, Yuqian Fu +8

Cross-Domain Few-Shot Object Detection (CD-FSOD) aims to detect novel objects with only a handful of labeled samples from previously unseen domains. While data augmentation and gen…