How We Built CoTracker3: Simpler and Better Point Tracking by Pseudo-Labeling Real Videos

CoTracker3 is a state-of-the-art point tracking model that introduces significant improvements in tracking objects through video sequences. Its key innovations include:

Use of semi-supervised training with real videos, reducing reliance on synthetic data
Generates pseudo-labels using existing tracking models as teachers
Features a simplified architecture compared to previous trackers

About the Speaker:
Nikita Karaev is currently doing a PhD at Meta AI and Oxford, where he’s working on dynamic reconstruction and motion estimation (CoTracker) with Andrea Vedaldi and Christian Rupprecht. Before that, he did his master’s at École Polytechnique (Paris), and undergrad in cold Siberia (Novosibirsk). He was also an early employee at two startups that got acquired by Snapchat and Farfetch.

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Recorded on Dec 12, 2024 at the AL, Machine Learning and Computer Vision Meetup.

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