GraspDiffusion: Synthesizing Realistic Whole-body Hand-Object Interaction

Understand

Recent generative models can synthesize high-quality images, but they often fail to generate humans interacting with objects using their hands.

• This arises mostly from the model's misunderstanding of such interactions and the hardships of synthesizing intricate regions of the body.
• In this paper, we propose \textbf{GraspDiffusion}, a novel generative method that creates realistic scenes of human-object interaction.
• Given a 3D object, GraspDiffusion constructs whole-body poses with control over the object's location relative to the human body, which is achieved by separately leveraging the generative priors for body and hand poses, optimizing them into a joint grasping pose.