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title
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2026-02-25 09:47:48
raw text
RoboDepth Challenge Welcome to sign up! User Name Email Password Confirm Password Verification Code Welcome back! User Name Password Login Intro Tracks Evaluation Awards Timeline Organizers Introduction Depth estimation from monocular and stereo images plays an essential role in real-world visual perception systems. Although promising results have been achieved, the current learning-based depth estimation models are trained and tested on clean datasets while ignoring the out-of-distribution (OoD) situations. Common corruptions, however, tend to happen in practical scenarios, which is safety-critical for applications like autonomous driving and robot navigation. To raise attention among the community to robust depth estimation, we propose the RoboDepth challenge. Our RoboDepth is the very first benchmark that targets probing the OoD robustness of depth estimation mo...
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