Research map / Video / Video segmentation and tracking
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase network depth from 16 to 28 layers (ablation) | Dynamic upsampling VSR network · Vid4 ×4 | PSNR: 26.81 -> 26.99 | Helped |
| Increase network depth from 16 to 52 layers (ablation) | Dynamic upsampling VSR network · Vid4 ×4 | PSNR: 26.81 -> 27.34 | Helped |
Closest papers by meaning
- Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling (AAAI 2021 · similarity 0.94)
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- SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network (AAAI 2024 · similarity 0.90)
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network (CVPR 2016 · similarity 0.89)
- Arbitrary-Scale Video Super-resolution Guided by Dynamic Context (AAAI 2024 · similarity 0.89)
- VideoGigaGAN: Towards Detail-rich Video Super-Resolution (CVPR 2025 · similarity 0.88)
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