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About Learning-Based Video Motion Magnification
1) The document presents a new learning-based approach for video motion magnification using deep convolutional neural networks. 2) Current techniques rely on hand-designed filters that may not be optimal, while the new approach learns filters directly from synthetic training data. 3) The learned filters achieve high-quality magnification of real videos with less noise and artifacts compared to previous methods.
Detailed Information
| Author: | ['Nur Arifin Akbar'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 16 |
| Language: | English |
| Format: | |
| Price: | FREE |
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