└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Video-Enhancement 2 | A list of resources for video enhancement, including video super-resolutio, interpolation, denoising, compression artifact removal et al.. 3 | 4 | By Yulun Zhang (yulun100@gmail.com), Yapeng Tian. (yapengtian@rochester.edu). If you have any suggestions, please contact us. Thanks! 5 | 6 | ## Video Interpolation 7 | * Xiaoyu Xiang et al., Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution, CVPR, 2020. [[Paper]](https://arxiv.org/abs/2002.11616) [[Code]](https://github.com/Mukosame/Zooming-Slow-Mo-CVPR-2020) 8 | 9 | * Huaizu Jiang et al., Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation, CVPR, 2018. [[Paper]](https://arxiv.org/abs/1712.00080) 10 | 11 | * Simon Niklaus et al., Context-aware Synthesis for Video Frame Interpolation, CVPR, 2018. [[Paper]](https://arxiv.org/abs/1803.10967) 12 | 13 | * Simone Meyer et al., PhaseNet for Video Frame Interpolation, CVPR, 2018. [[Paper]](https://arxiv.org/abs/1804.00884) 14 | 15 | * Tianfan Xue et al., Video Enhancement with Task-Oriented Flow, arXiv, 2017. [[Paper]](https://arxiv.org/abs/1711.09078) [[Code]](http://toflow.csail.mit.edu/) 16 | 17 | * Simon Niklaus et al., Video Frame Interpolation via Adaptive Separable Convolution, ICCV, 2017. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Niklaus_Video_Frame_Interpolation_ICCV_2017_paper.pdf) [[Code]](https://github.com/sniklaus/pytorch-sepconv) 18 | 19 | * Ziwei Liu et al., Video Frame Synthesis using Deep Voxel Flow, ICCV, 2017. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Liu_Video_Frame_Synthesis_ICCV_2017_paper.pdf) 20 | 21 | ## Video Super-Resolution 22 | * Xiaoyu Xiang et al., Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution, CVPR, 2020. [[Paper]](https://arxiv.org/abs/2002.11616) [[Code]](https://github.com/Mukosame/Zooming-Slow-Mo-CVPR-2020) 23 | 24 | * Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, Chen Change Loy. EDVR: Video Restoration with Enhanced Deformable Convolutional Networks, CVPRW, 2019. [[Paper]](https://arxiv.org/pdf/1905.02716.pdf) [[Code]](https://github.com/xinntao/EDVR) 25 | 26 | * Yapeng Tian, Yulun Zhang, Yun Fu, Chenliang Xu. TDAN: Temporally Deformable Alignment Network for Video Super-Resolution, ArXiv, 2018. [[Paper]](https://arxiv.org/pdf/1812.02898.pdf) [[Demo]](https://www.youtube.com/watch?v=eZExENE50I0) [[Code]](https://github.com/YapengTian/TDAN_VSR) 27 | 28 | * Younghyun Jo et al., Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation, CVPR, 2018. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Jo_Deep_Video_Super-Resolution_CVPR_2018_paper.pdf) 29 | 30 | * Mehdi S. M. Sajjadi et al., Frame-Recurrent Video Super-Resolution, CVPR, 2018. [[Paper]](https://arxiv.org/pdf/1801.04590.pdf) 31 | 32 | * Xin Tao et al., Detail-Revealing Deep Video Super-Resolution, ICCV, 2017. [[Paper]](https://arxiv.org/abs/1704.02738) [[Code]](https://github.com/jiangsutx/SPMC_VideoSR) 33 | 34 | * Ding Liu et al., Robust Video Super-Resolution With Learned Temporal Dynamics, ICCV, 2017. [[Paper]](https://arxiv.org/abs/1704.02738) 35 | 36 | * Renjie Liao et al., Video Super-Resolution via Deep Draft-Ensemble Learning, ICCV, 2015. [[Paper]](http://www.cse.cuhk.edu.hk/leojia/projects/DeepSR/papers/DeepSR_final.pdf) [[Code]](http://www.cse.cuhk.edu.hk/leojia/projects/DeepSR/) 37 | 38 | 39 | ## Video Denoising 40 | * Bihan Wen et al., Joint Adaptive Sparsity and Low-Rankness on the Fly: An Online Tensor Reconstruction Scheme for Video Denoising, ICCV, 2017. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Wen_Joint_Adaptive_Sparsity_ICCV_2017_paper.pdf) 41 | * Matias Tassano et al., FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation, CVPR, 2020. [[Paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Tassano_FastDVDnet_Towards_Real-Time_Deep_Video_Denoising_Without_Flow_Estimation_CVPR_2020_paper.pdf) [[Code]](https://github.com/m-tassano/fastdvdnet) 42 | 43 | ## Video Deblurring 44 | * Seungjun Nah et al., Recurrent Neural Networks with Intra-Frame Iterations for Video Deblurring, CVPR, 2019. [[Paper]]() 45 | 46 | * Wenqi Ren et al., Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel, ICCV, 2017. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Ren_Video_Deblurring_via_ICCV_2017_paper.pdf) 47 | 48 | * Tae Hyun Kim et al., Online Video Deblurring via Dynamic Temporal Blending Network, ICCV, 2017. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Kim_Online_Video_Deblurring_ICCV_2017_paper.pdf) 49 | 50 | ## Other Video Enhancement Tasks 51 | * Ren Yang et al., Multi-Frame Quality Enhancement for Compressed Video, CVPR, 2018. [[Paper]](https://arxiv.org/abs/1803.04680) 52 | --------------------------------------------------------------------------------