Feb 1, 2024 · In this work, we demonstrate how large-scale, unlabeled, uncurated real-world data can improve a TAP model with minimal architectural changes.

To endow models with greater understanding of physics and motion, it is useful to enable them to perceive how solid surfaces move and deform in real scenes.

Feb 1, 2024 · In this work, we demonstrate how large-scale, unlabeled, uncurated real-world data can improve a TAP model with minimal architectural changes.

After initializing a TAPIR model with standard supervised training, we bootstrap the model on real data by adding an additional self-supervised loss. We apply a ...

Dec 8, 2024 · To endow models with greater understanding of physics and motion, it is useful to enable them to perceive how solid surfaces move and deform ...

After tracking points, we identify query points that are on the 'front side' of an occlusion boundary: that is, any neighboring pixel which is more than 105% of ...

Dec 10, 2024 · This paper investigates bootstrapping for statistical parsers to reduce their reliance on manually annotated training data. We consider both a ...

Feb 1, 2024 · This work demonstrates how large-scale, unlabeled, uncurated real-world data can improve a TAP model with minimal architectural changes, ...

Missing: BootsTRAP: | Show results with:BootsTRAP:

May 23, 2024 · To endow models with greater understanding of physics and motion, it is useful to enable them to perceive how solid surfaces move and deform ...