PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions

Inferring programs which generate 2D and 3D shapes is important for reverse engineering, editing, and more. Training models to perform this task is complicated because paired (shape, program) data is not readily available for many domains, making exact supervised learning infeasible. However, it is...

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Bibliographic Details

Published in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 9861 - 9870
Main Authors:	Jones, R. Kenny, Walke, Homer, Ritchie, Daniel
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2022
Subjects:	grouping and shape analysis Predictive models Reinforcement learning Reverse engineering Self-& semi-& meta- Deep learning architectures and techniques; Machine learning; Segmentation Shape Supervised learning Three-dimensional displays Training
ISSN:	1063-6919
Online Access:	Get full text
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