Related papers: Learning to Assemble Geometric Shapes

Learning to Assemble Geometric Shapes

URL: http://arxiv.org/abs/2205.11809v1
Date: Tue, 24 May 2022 06:07:13 GMT
Title: Learning to Assemble Geometric Shapes
Authors: Jinhwi Lee and Jungtaek Kim and Hyunsoo Chung and Jaesik Park and Minsu Cho
Abstract summary: Assembling parts into an object is a problem that arises in a variety of contexts in the real world and involves numerous applications in science and engineering. Previous work tackles limited cases with identical unit parts or jigsaw-style parts of textured shapes. In this work, we introduce the more challenging problem of shape assembly, which involves textureless fragments of arbitrary shapes with indistinctive junctions.
Score: 40.2815083025929
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Assembling parts into an object is a combinatorial problem that arises in a variety of contexts in the real world and involves numerous applications in science and engineering. Previous related work tackles limited cases with identical unit parts or jigsaw-style parts of textured shapes, which greatly mitigate combinatorial challenges of the problem. In this work, we introduce the more challenging problem of shape assembly, which involves textureless fragments of arbitrary shapes with indistinctive junctions, and then propose a learning-based approach to solving it. We demonstrate the effectiveness on shape assembly tasks with various scenarios, including the ones with abnormal fragments (e.g., missing and distorted), the different number of fragments, and different rotation discretization.

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