Paper Info
Title
Self-Supervision for 3D Real-World Challenges.
Abstract
We consider several possible scenarios involving synthetic and real-world point clouds where supervised learning fails due to data scarcity and large domain gaps. We propose to enrich standard feature representations by leveraging self-supervision through a multi-task model that can solve a 3D puzzle while learning the main task of shape classification or part segmentation.
Year
DOI
Venue
2020
10.1007/978-3-030-66415-2_48
ECCV Workshops
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Antonio Alliegro101.01
Davide Boscaini232015.28
Tatiana Tommasi350229.31