Starting from Non-Parametric Networks for 3D Point Cloud Analysis
Author:
Affiliation:
1. CUHK MMLab
2. Peking University
3. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
4. Shanghai Artificial Intelligence Laboratory
5. University of Pennsylvania
Funder
National Key R&D Program of China
Innovation and Technology Commission (ITC)'s InnoHK
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203175.pdf?arnumber=10203175
Reference44 articles.
1. Pointcnn: Convolution on x-transformed points;li;Advances in neural information processing systems,2018
2. Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling;wu;Proceedings of the 30th International Confer-ence on Neural Information Processing Systems,0
3. Pedestrian recognition using high-definition LIDAR
4. Dynamic Graph CNN for Learning on Point Clouds
5. Relation-Shape Convolutional Neural Network for Point Cloud Analysis
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