PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Author:
Affiliation:
1. Computer Vision Lab of ETH Zurich, Zürich, Switzerland
2. University of Würzburg in Germany, Würzburg, Germany
Funder
ETH Zürich Fund
Nvidia GPU grant
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/ielx7/34/10169863/10054148.pdf?arnumber=10054148
Reference106 articles.
1. Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences
2. Learning to Compose Hypercolumns for Visual Correspondence
3. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
4. FlowNet: Learning Optical Flow with Convolutional Networks
5. Convolutional Neural Network Architecture for Geometric Matching
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