OpenEDS Challenge

OpenEDS Challenge

Immersive AR/VR demands unprecedented eye tracking performance. Eye tracking must be precise, accurate, and work all the time, for every person, in any environment. While advancements in deep learning have yielded successes in domains with similar challenges, the real time requirement and platform power limitations put serious memory and compute constraints on any ML-based solution. Additionally, a robust and efficient ML solution that is insensitive to environmental factors requires large amounts of highly accurate ground-truth training data from thousands of users in challenging conditions. Unfortunately, capturing accurate eye-gaze data in these environments requires a highly sophisticated and costly setup, and even with this setup, accuracy is limited by user fixation ability and cooperation. These issues place practical limitations on the amount and quality of training data that can be collected.

Awards:- $260,000

Deadline:- 15-09-2019

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