Global Matching with Overlapping Attention for Optical Flow Estimation
Author:
Affiliation:
1. Rutgers University
2. Google Research
3. Sense Time Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878735.pdf?arnumber=9878735
Reference55 articles.
1. Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation
2. PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
3. Stand-alone self-attention in vision models;ramachandran;NeurIPS,2019
4. PyTorch: An imperative style, high-performance deep learning library;paszke;NeurIPS,2019
5. Highly Accurate Optic Flow Computation with Theoretically Justified Warping
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