RoSHI is a hybrid wearable that combines sparse IMUs and egocentric SLAM to capture accurate full-body 3D pose and shape data in natural environments for robot learning.
Karen Liu, Ziwei Liu, Jakob Engel, Renzo De Nardi, and Richard Newcombe
4 Pith papers cite this work. Polarity classification is still indexing.
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BoxerNet lifts 2D bounding boxes to metric 3D boxes via transformer regression with aleatoric uncertainty and median depth encoding, then fuses multi-view results to outperform CuTR by large margins on open-world benchmarks.
SAM 3D reconstructs 3D objects from single images with geometry, texture, and pose using human-model annotated data at scale and synthetic-to-real training, achieving 5:1 human preference wins.
The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.
citing papers explorer
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RoSHI: A Versatile Robot-oriented Suit for Human Data In-the-Wild
RoSHI is a hybrid wearable that combines sparse IMUs and egocentric SLAM to capture accurate full-body 3D pose and shape data in natural environments for robot learning.
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Boxer: Robust Lifting of Open-World 2D Bounding Boxes to 3D
BoxerNet lifts 2D bounding boxes to metric 3D boxes via transformer regression with aleatoric uncertainty and median depth encoding, then fuses multi-view results to outperform CuTR by large margins on open-world benchmarks.
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SAM 3D: 3Dfy Anything in Images
SAM 3D reconstructs 3D objects from single images with geometry, texture, and pose using human-model annotated data at scale and synthetic-to-real training, achieving 5:1 human preference wins.
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World Action Models: The Next Frontier in Embodied AI
The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.