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title
Category-Level Articulated Object Pose Estimation
description
This project addresses the task of category-level pose estimation for articulated objects from a single depth image. We present a novel category-level approach that correctly accommodates object insta
site name
author
updated
2026-02-17 07:06:22
raw text
Category-level Category-Level Articulated Object Pose Estimation CVPR 2020(Oral) This project addresses the task of category-level pose estimation for articulated objects from a single depth image. We present a novel category-level approach that correctly accommodates object instances previously unseen during training. We introduce Articulation-aware NormalizedCoordinate Space Hierarchy (ANCSH) – a canonical representation for different articulated objects in a given category. As the key to achieve intra-category generalization, the representation constructs a canonical objectspace as well as a set of canonical part spaces. Thecanonical object space normalizes the object orientation,scales and articulations (e.g. joint parameters and states) while each canonical part space further normalizes its part pose and scale. We develop a deep network based on PointNet++ that predicts ANCSH from a single depth pointcloud, including part segmentation, normalized coor...
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