arXiv AI June 17, 2026 By Edoardo Bianchi, Antonio Liotta

SkillMoV: Mixture-of-View Routing with Prototype-Conditioned Gating for Unified Multi-View Proficiency Estimation

arXiv:2606. 17615v1 Announce Type: cross Abstract: Estimating human proficiency from video is a key challenge for automated skill assessment, with applications in sports coaching, music pedagogy, surgical training, and workplace learning.

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arXiv AI

Jul 1

SkillSpotter: Pose-Aware Multi-View Skilled Action Detection and Grading in Ego-Exo Videos

arXiv:2606. 31127v1 Announce Type: cross Abstract: To enable personalized, real-time coaching using Augmented Reality glasses or fixed camera setups in domains such as sports, cooking, or music, a system must understand not just what a person does, but how well they execute an activity.

By Bj\"orn Braun, Christian Holz

benchmarks

arXiv Computer Vision

Aug 27

Moving Beyond More Views: Redundancy-Aware Ego-Exo Fusion for Proficiency Estimation

The paper introduces a redundancy-aware fusion framework for EgoExo proficiency estimation, which integrates fine-grained motion cues from egocentric views with spatial context from exocentric views. It identifies multiview redundancy and overfitting as key challenges and proposes two modules—AdaMVS for adaptive view selection and VIB-GB for compressing redundant signals—to address them. Experiments on EgoExo-4D and EgoExo-Fitness show that the method learns to select informative views and fuse them effectively, achieving state‑of‑the‑art results.

By Xu Dong, Wanqing Li, Anthony Adeyemi-Ejeye, Andrew Gilbert

benchmarks

arXiv Computer Vision

Sep 22

CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning

arXiv:2609.23492v1 Announce Type: new Abstract: Perception for embodied agents is video-based, often multi-view (ego, exo, or both), and inherently continual, with simultaneous task and viewpoint shi...

By Hongwei Yan, Kanglei Zhou, Yuchen Liu, Qingyu Shi, Yi Zhong, Liyuan Wang

agents computer-vision robotics benchmarks

arXiv AI

4d ago

Does Local Video Understanding Transfer Across Encounters? The EgoGears Benchmark

arXiv:2609.37938v1 Announce Type: cross Abstract: Embodied systems must make knowledge acquired during one encounter usable in another despite changes in viewpoint, motion, and illumination. Yet aggr...

By Yuedong Tan, Lei Qi, Yu Liu, Di Wen, Ruiping Liu, Xiaoye Wang, Yufan Chen, Junwei Zheng, Chengzhi Wu, Chen Zhang, Zhihang Chen, Haiwen Sun, Zongwei Wu, Radu Timofte, Danda Pani Paudel, Kunyu Peng

robotics benchmarks safety

arXiv Machine Learning

Jun 19

UNIEGO: Proxies as Mediators for Unified Egocentric Video Representation Learning

arXiv:2606. 20559v1 Announce Type: cross Abstract: Egocentric video understanding is inherently limited by the narrow perspective of wearable cameras: a single viewpoint, a single modality, a single model cannot capture the full richness of human action.

By Wenhao Chi, Arkaprava Sinha, Dominick Reilly, Hieu Le, Srijan Das

computer-vision efficiency benchmarks

arXiv Machine Learning

Aug 26

MoTE: Mixture of Task Experts for Multi-Task Video Understanding

arXiv:2608.24763v1 Announce Type: cross Abstract: Procedural video-language models must solve heterogeneous tasks from the same visual evidence, including action recognition, forecasting, and procedu...

By Muhammad Asad Ali, Umar Khan, Nadia Robertini, Didier Stricker

llms multimodal benchmarks