EgoBrain: Egocentric Action Understanding with Gaze-Mind Synergy

EgoBrain is an egocentric vision dataset for human action understanding developed by the University of Tokyo and Microsoft Research Asia for ICLR 2026. It provides multimodal data focusing on the synergy between visual attention and cognitive processes during physical activities.

Use Cases

• Training action recognition models using gaze-based attention features
• Analyzing human visual search patterns during complex physical tasks
• Developing multimodal egocentric vision systems linking intent and perception

Strengths

• Collaborative research output from University of Tokyo and Microsoft Research Asia
• Peer-reviewed for ICLR 2026
• Integrates gaze-tracking data with action labels

Limitations

• Metadata lacks specific row counts and file size details
• Restricted to non-commercial use under CC BY-NC 4.0 license

Provenance

Source

University of Tokyo and Microsoft Research Asia (ICLR 2026)

Collection Method

Sensor-based egocentric recording and annotation

Freshness

Last updated March 2026, corresponding with the ICLR 2026 conference cycle.