mmediting/configs/restorers/iconvsr

• IconVSR (CVPR'2021)
• • Abstract
  • Results and models
  • Citation

IconVSR (CVPR'2021)

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

Abstract

Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not uncommon. In this study, we wish to untangle the knots and reconsider some most essential components for VSR guided by four basic functionalities, i.e., Propagation, Alignment, Aggregation, and Upsampling. By reusing some existing components added with minimal redesigns, we show a succinct pipeline, BasicVSR, that achieves appealing improvements in terms of speed and restoration quality in comparison to many state-of-the-art algorithms. We conduct systematic analysis to explain how such gain can be obtained and discuss the pitfalls. We further show the extensibility of BasicVSR by presenting an information-refill mechanism and a coupled propagation scheme to facilitate information aggregation. The BasicVSR and its extension, IconVSR, can serve as strong baselines for future VSR approaches.

Results and models

Evaluated on RGB channels for REDS4 and Y channel for others. The metrics are PSNR / SSIM .
The pretrained weights of the IconVSR components can be found here: SPyNet, EDVR-M for REDS, and EDVR-M for Vimeo-90K.

Method	REDS4 (BIx4) PSNR/SSIM (RGB)	Vimeo-90K-T (BIx4) PSNR/SSIM (Y)	Vid4 (BIx4) PSNR/SSIM (Y)	UDM10 (BDx4) PSNR/SSIM (Y)	Vimeo-90K-T (BDx4) PSNR/SSIM (Y)	Vid4 (BDx4) PSNR/SSIM (Y)	Download
iconvsr_reds4	31.6926/0.8951	36.4983/0.9416	27.4809/0.8354	35.3377/0.9471	34.4299/0.9287	25.2110/0.7732	model | log
iconvsr_vimeo90k_bi	30.3452/0.8659	37.3729/0.9467	27.4238/0.8297	34.2595/0.9398	34.5548/0.9295	24.6666/0.7491	model | log
iconvsr_vimeo90k_bd	29.0150/0.8465	34.6780/0.9339	26.3109/0.8028	40.0640/0.9697	37.7573/0.9517	28.2464/0.8612	model | log

Citation

@InProceedings{chan2021basicvsr,
  author = {Chan, Kelvin CK and Wang, Xintao and Yu, Ke and Dong, Chao and Loy, Chen Change},
  title = {BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond},
  booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition},
  year = {2021}
}