Dex2HOI is a dual-stream diffusion model with bidirectional cross-attention and motion fusion that generates long bimanual single- and two-object HOI sequences from text at real-time speeds.
Hoidini: Human-object interaction through diffusion noise optimization
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A text-conditioned diffusion model using dynamic object-centric BPS, mixed-domain training, and contact augmentation produces generalizable full-body locomotion-to-articulated-object interaction sequences that beat adapted baselines on contact and pose metrics.
MOCHI enhances noisy collaborative human-object interaction captures via grasp optimization followed by diffusion-based full-body refinement that incorporates interaction information into single-person motion priors.
PhyGenHOI couples a motion diffusion model for humans with material point method simulation for objects on 3D Gaussians, using attraction loss, contact re-simulation, and masked video-SDS to produce physically consistent dynamic interactions from text.
A single constant initial noise vector found by Monte-Carlo search improves frozen diffusion and flow-matching robot policies on 46 of 51 tasks, by up to 55% absolute success rate.
citing papers explorer
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Dex2HOI: Dexterous Bimanual Two-Object Interaction Generation
Dex2HOI is a dual-stream diffusion model with bidirectional cross-attention and motion fusion that generates long bimanual single- and two-object HOI sequences from text at real-time speeds.
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GIRAF: Towards Generalizable Human Interactions with Articulated Objects
A text-conditioned diffusion model using dynamic object-centric BPS, mixed-domain training, and contact augmentation produces generalizable full-body locomotion-to-articulated-object interaction sequences that beat adapted baselines on contact and pose metrics.
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MOCHI: Motion Enhancement of Collaborative Human-object Interactions
MOCHI enhances noisy collaborative human-object interaction captures via grasp optimization followed by diffusion-based full-body refinement that incorporates interaction information into single-person motion priors.
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PhyGenHOI: Physically-Aware 4D Generation of Dynamic Human-Object Interactions
PhyGenHOI couples a motion diffusion model for humans with material point method simulation for objects on 3D Gaussians, using attraction loss, contact re-simulation, and masked video-SDS to produce physically consistent dynamic interactions from text.
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You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector
A single constant initial noise vector found by Monte-Carlo search improves frozen diffusion and flow-matching robot policies on 46 of 51 tasks, by up to 55% absolute success rate.