BlockNet: A Deep Neural Network for Block-Based Motion Estimation Using Representative Matching
Abstract
1. Introduction
2. BlockNet
2.1. Feature Extractor
2.2. Representative Matching for Motion Estimation
2.2.1. Proposed Algorithm
2.2.2. Implementation Details
Algorithm 1. Proposed representative matching |
Definition |
: The average-pooling operator |
: Duplication of each element of the matrix |
: Extraction of the patches repeatedly |
Input: current feature , reference feature , block size , and search range |
Output: |
2.3. Pyramidal Structure with Feature Warping
3. Experiments
3.1. Experimental Setup
3.2. Results
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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BME with Full Matching | BME with Proposed RM | BlockNet with Full Matching | BlockNet with Proposed RM | |
---|---|---|---|---|
Average EPE | 10.33 | 16.86 | 3.74 | 4.09 |
Std. of EPE | 7.64 | 7.09 | 3.53 | 3.57 |
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Lee, J.; Kong, K.; Bae, G.; Song, W.-J. BlockNet: A Deep Neural Network for Block-Based Motion Estimation Using Representative Matching. Symmetry 2020, 12, 840. https://doi.org/10.3390/sym12050840
Lee J, Kong K, Bae G, Song W-J. BlockNet: A Deep Neural Network for Block-Based Motion Estimation Using Representative Matching. Symmetry. 2020; 12(5):840. https://doi.org/10.3390/sym12050840
Chicago/Turabian StyleLee, Junggi, Kyeongbo Kong, Gyujin Bae, and Woo-Jin Song. 2020. "BlockNet: A Deep Neural Network for Block-Based Motion Estimation Using Representative Matching" Symmetry 12, no. 5: 840. https://doi.org/10.3390/sym12050840
APA StyleLee, J., Kong, K., Bae, G., & Song, W.-J. (2020). BlockNet: A Deep Neural Network for Block-Based Motion Estimation Using Representative Matching. Symmetry, 12(5), 840. https://doi.org/10.3390/sym12050840