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Achieving state-of-the-art hair dynamics in head avatars, DynHair allows for realistic and controllable hair movement that adapts to head motion.
A new dataset and transformer model that together nearly double the success rate for 3D hand-object pose estimation in real-world settings.
IMAGIN-4D enables unprecedented fine-grained control over human-object interactions by leveraging spatio-temporal image conditioning, outperforming traditional methods that rely on single-token representations.
Contact-aware reconstruction transforms how we achieve realistic human-scene interactions in 3D environments, correcting artifacts that have plagued previous methods.
