Deep Scene Flow Learning: From 2D Images to 3D Point Clouds
Author:
Affiliation:
1. School of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
2. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada
Funder
National Natural Science Foundation of China
Natural Science Foundation of Heilongjiang Province
Fundamental Research Funds for the Central Universities
Chinese Association for Artificial Intelligence (CAAI)-Huawei MindSpore Open Fund
Key Laboratory Open Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/10345401/10264132.pdf?arnumber=10264132
Reference191 articles.
1. Scene Flow from Point Clouds with or without Learning
2. Unsupervised Learning of Depth, Optical Flow and Pose With Occlusion From 3D Geometry
3. Optical Flow in Mostly Rigid Scenes
4. Online multi-object tracking combining optical flow and compressive tracking in Markov decision process
5. Moving Object Tracking Based on Sparse Optical Flow with Moving Window and Target Estimator
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