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Found 4 papers, 1 papers with code
Zero-Shot Learning for the Primitives of 3D Affordance in General Objects
One of the major challenges in AI is teaching machines to precisely respond and utilize environmental functionalities, thereby achieving the affordance awareness that humans possess.
CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images
We present multiple strategies to leverage the synthesized images, including (1) the first method to leverage a generative image model for 3D human-object spatial relation learning; (2) a framework to reason about the 3D spatial relations from inconsistent 2D cues in a self-supervised manner via 3D occupancy reasoning with pose canonicalization; (3) semantic clustering to disambiguate different types of interactions with the same object types; and (4) a novel metric to assess the quality of 3D spatial learning of interaction.
Common Sense Reasoning
Human-Object Interaction Detection
+1
Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Models
We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars.
CHORUS : Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images
We present multiple strategies to leverage the synthesized images, including (1) the first method to leverage a generative image model for 3D human-object spatial relation learning; (2) a framework to reason about the 3D spatial relations from inconsistent 2D cues in a self-supervised manner via 3D occupancy reasoning with pose canonicalization; (3) semantic clustering to disambiguate different types of interactions with the same object types; and (4) a novel metric to assess the quality of 3D spatial learning of interaction.
Common Sense Reasoning
Human-Object Interaction Detection
+1
