arXiv Machine Learning By Qiance Tang, Ziqi Wang, Jieyu Lin, Ziyun Li, Barbara De Salvo, Sai Qian Zhang

EgoEverything: A Benchmark for Human Behavior Inspired Long Context Egocentric Video Understanding in AR Environment

Read the original on arXiv Machine Learning →

arXiv:2604. 08342v2 Announce Type: replace Abstract: Long context egocentric video understanding has recently attracted significant research attention, with augmented reality (AR) highlighted as one of its most important application domains.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 29

EXPLORE-Bench: Egocentric Scene Prediction with Long-Horizon Reasoning

arXiv:2603. 09731v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are increasingly considered as a foundation for embodied agents, yet it remains unclear whether they can reliably reason about the long-term physical consequences of actions from an egocentric viewpoint.

By Chengjun Yu, Xuhan Zhu, Chaoqun Du, Pengfei Yu, Wei Zhai, Yang Cao, Zheng-Jun Zha
arXiv AI
Aug 6

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

arXiv:2608. 04589v1 Announce Type: cross Abstract: EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize beyond common daily-life scenarios.

By Yuqian Fu, Tianwen Qian, Yanjun Li, Yu Li, Kunyu Peng, Xu Zheng, Yongqin Xian, Alessio Tonioni, Yanwei Fu, Xiaoling Wang, Danda Paudel, Federico Tombari, Luc Van Gool, Leyi Wu, Yifan Zhao, Jinjie Zhang, Yinchuan Li, Yingcong Chen, Zixu Li, Zhiwei Chen, Zhiheng Fu, Wenbo Wang, Yupeng Hu, Weili Guan, Liqiang Nie, Takuya Murakawa, Toru Tamaki, Yi Wen, Zhenglin Du, Zhengyang Li, Lingling Li, Licheng Jiao, Wenping Ma
arXiv AI
Jul 2

EgoGapBench: Benchmarking Egocentric Action Selection in Multi-Agent Scenes

arXiv:2607. 00547v1 Announce Type: cross Abstract: Existing egocentric benchmarks have primarily constructed the egocentric setting from first-person-view data, which makes it difficult to evaluate egocentric perspective itself in isolation.

By Jihyeok Jung (KAIST AI), Jeewu Lee (Sogang University), Sanghyeop Kim (Sogang University), Chanhee Han (Ministry of Science and ICT), Seong Joon Oh (KAIST AI)