Based on paperwithcode VSR task, this repository contains summary of the state-of-the-art VSR methods.
| Model | Published | Code | Year | Vid4 Y - 4x (PSNR) | | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ | ---- | ------------------ | | RRN-L | [arXiv][RRN-Lpaperlink] | - | 2020 | 27.69 | | iSeeBetter | [Computational Visual Media][iSeeBetterpaperlink] | [PyTorch][iSeeBettercodelink] | 2020 | 27.43 | | PFNL | [ICCV19][PFNLpaperlink] | [TensorFlow][PFNLcodelink] | 2019 | 27.40 | | ADNLVSR | [Neurocomputing][ADNLVSRpaperlink] | - | 2020 | 27.39 | | EDVR | [CVPR19][EDVRpaperlink] | [PyTorch][EDVRcodelink] | 2019 | 27.35 | | VSR-DUF | [CVPR18][VSR-DUFpaperlink] | [TensorFlow][VSR-DUFcodelink] | 2018 | 27.31 | | RBPN/6-PF | [CVPR19][RBPN/6-PFpaperlink] | [PyTorch][RBPN/6-PFcodelink] | 2019 | 27.12 | | TDAN | [CVPR20][TDANpaperlink] | [PyTorch][TDANcodelink] | 2020 | 26.86 | | FRVSR | [CVPR18][FRVSRpaperlink] | - | 2018 | 26.69 | | WDVR | [CVPR19][WDVRpaperlink] | [PyTorch][WDVRcodelink] | 2019 | 26.62 | | MDCN | [Neurocomputing][MDCNpaperlink] | - | 2019 | 26.49 | | DDAN | [IEEE Transactions on Image Processing][DDANpaperlink] | - | 2020 | 26.48 | | SOF-VSR | [IEEE Transactions on Image Processing][SOF-VSRpaperlink] | [PyTorch][SOF-VSRcodelink] | 2020 | 26.01 | | DRDVSR | [ICCV17][DRDVSRpaperlink] | [TensorFlow][DRDVSRcodelink] | 2017 | 25.88 | | VESPCN | [CVPR17][VESPCNpaperlink] | - | 2017 | 25.35 | | Bicubic (Baseline) | | | | 23.82 |- RRN-L
- iSeeBetter
- PFNL
- ADNLVSR
- EDVR
- VSR-DUF
- RBPN/6-PF
- TDAN
- FRVSR
- WDVR
- MDCN
- DDAN
- SOF-VSR
- DRDVSR
- VESPCN
Please refer to Dataset.md for more details.
- Isobe, Takashi, Fang Zhu, and Shengjin Wang. "Revisiting Temporal Modeling for Video Super-resolution." arXiv preprint arXiv:2008.05765 (2020).
- Chadha, Aman, John Britto, and M. Mani Roja. "iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networks." Computational Visual Media (2020): 1-12.
- Yi, Peng, et al. "Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations." Proceedings of the IEEE International Conference on Computer Vision. 2019.
- Sun, Wei, and Yanning Zhang. "Attention-guided Dual Spatial-Temporal Non-local Network for Video Super-Resolution." Neurocomputing (2020).
- Wang, Xintao, et al. "Edvr: Video restoration with enhanced deformable convolutional networks." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2019.
- Jo, Younghyun, et al. "Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
- Haris, Muhammad, Gregory Shakhnarovich, and Norimichi Ukita. "Recurrent back-projection network for video super-resolution." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019.
- Tian, Yapeng, et al. "TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020.
- Sajjadi, Mehdi SM, Raviteja Vemulapalli, and Matthew Brown. "Frame-recurrent video super-resolution." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.
- Fan, Yuchen, et al. "An Empirical Investigation of Efficient Spatio-Temporal Modeling in Video Restoration." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2019.
- Purohit, Kuldeep, Srimanta Mandal, and A. N. Rajagopalan. "Mixed-dense connection networks for image and video super-resolution." Neurocomputing (2019).
- Li, Feng, Huihui Bai, and Yao Zhao. "Learning a Deep Dual Attention Network for Video Super-Resolution." IEEE Transactions on Image Processing 29 (2020): 4474-4488.
- Wang, Longguang, et al. "Deep Video Super-Resolution using HR Optical Flow Estimation." arXiv preprint arXiv:2001.02129 (2020).
- Tao, Xin, et al. "Detail-revealing deep video super-resolution." Proceedings of the IEEE International Conference on Computer Vision. 2017.
- Caballero, Jose, et al. "Real-time video super-resolution with spatio-temporal networks and motion compensation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017.