CF-SIS: Semantic-Instance Segmentation of 3D Point Clouds by Context Fusion with Self-Attention
Author:
Affiliation:
1. Tsinghua University, Beijing, China
2. University of Maryland, College Park, College Park, MD, USA
Funder
National Key R&D Program of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3394171.3413829
Reference42 articles.
1. Iro Armeni Sasha Sax Amir R Zamir and Silvio Savarese. 2017. Joint 2D-3D-semantic data for indoor scene understanding. arXiv preprint arXiv:1702.01105 (2017). Iro Armeni Sasha Sax Amir R Zamir and Silvio Savarese. 2017. Joint 2D-3D-semantic data for indoor scene understanding. arXiv preprint arXiv:1702.01105 (2017).
2. Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views
3. 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation
4. View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions
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