EgoInteract is a new simulator for generating synthetic egocentric videos with precise control over camera, body, hand, and object motions, producing a dataset that improves model performance on real-world benchmarks for temporal action segmentation, next-active object detection, interaction Anticip
Egocontrol: Controllable egocentric video generation via 3d full-body poses
4 Pith papers cite this work. Polarity classification is still indexing.
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DreamDojo is a foundation world model pretrained on the largest human video dataset to date that uses continuous latent actions to transfer interaction knowledge and achieves controllable physics simulation after robot post-training.
A new occlusion-aware control module generates high-fidelity egocentric videos from sparse 3D hand joints, supported by a million-clip dataset and cross-embodiment benchmark.
citing papers explorer
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EgoInteract: Synthetic Egocentric Videos Generation for Interaction Understanding and Anticipation
EgoInteract is a new simulator for generating synthetic egocentric videos with precise control over camera, body, hand, and object motions, producing a dataset that improves model performance on real-world benchmarks for temporal action segmentation, next-active object detection, interaction Anticip
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DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos
DreamDojo is a foundation world model pretrained on the largest human video dataset to date that uses continuous latent actions to transfer interaction knowledge and achieves controllable physics simulation after robot post-training.
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Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints
A new occlusion-aware control module generates high-fidelity egocentric videos from sparse 3D hand joints, supported by a million-clip dataset and cross-embodiment benchmark.
- EgoExo-WM: Unlocking Exo Video for Ego World Models