两支研究团队在EgoVis 2026会议的挑战赛中提交了技术报告。其中，JFAA团队使用基于JEPA的方法进行未来动作预测，在EPIC-KITCHENS-100动作预测挑战赛中获得第一名。第二支团队MARS团队将CASTLE挑战赛视为一个跨越视频、文字记录和传感器数据等多种模态的代理证据选择问题，并利用GPT-5.4决策代理，在该挑战赛中获得第二名。 AI
影响 展示了多模态推理和动作预测方面的进展，可能影响未来的具身AI研究。
排序理由 两份技术报告详细介绍了在学术挑战赛中获得顶尖排名的AI系统。
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We propose JFAA, a JEPA-based Future Action Anticipation method for the EPIC-KITCHENS-100 (EK-100) Action Anticipation task. Inspired by the representation learning and future prediction ability of V-JEPA 2.1, JFAA uses a frozen encoder and predictor to extract observed context f…
We propose JFAA, a JEPA-based Future Action Anticipation method for the EPIC-KITCHENS-100 (EK-100) Action Anticipation task. Inspired by the representation learning and future prediction ability of V-JEPA 2.1, JFAA uses a frozen encoder and predictor to extract observed context f…
This report presents MARS, short for Multimodal Agentic Reasoning with Source selection, our system for the CASTLE Challenge at EgoVis 2026. Participants must answer 185 closed-form questions over the CASTLE 2024 dataset. In contrast to prior single-video egocentric benchmarks, C…