In this work, we focus on a novel task of category-level functional
hand-object manipulation synthesis covering both rigid and articulated object
categories. Given an object geometry, an initial human hand pose as well as a
sparse control sequence of object poses, our goal is to generate a physically
reasonable hand-object manipulation sequence that performs like human beings.
To address such a challenge, we first design CAnonicalized Manipulation Spaces
(CAMS), a two-level space hierarchy that canonicalizes the hand poses in an
object-centric and contact-centric view. Benefiting from the representation
capability of CAMS, we then present a two-stage framework for synthesizing
human-like manipulation animations. Our framework achieves state-of-the-art
performance for both rigid and articulated categories with impressive visual
effects. Codes and video results can be found at our project homepage:
https://cams-hoi.github.io/Comment: CVPR 2023 Receive