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abikaki committed Feb 21, 2024
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<a href="https://github.com/DmitryRyumin/CVPR-2023-Papers/blob/main/sections/2023/main/low-level-vision.md">Low-Level Vision</a>
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12 changes: 6 additions & 6 deletions sections/2023/main/low-level-vision.md
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| Structured Sparsity Learning for Efficient Video Super-Resolution | [![GitHub](https://img.shields.io/github/stars/Zj-BinXia/SSL?style=flat)](https://github.com/Zj-BinXia/SSL) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Xia_Structured_Sparsity_Learning_for_Efficient_Video_Super-Resolution_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2206.07687-b31b1b.svg)](http://arxiv.org/abs/2206.07687) | :heavy_minus_sign: |
| DNeRV: Modeling Inherent Dynamics via Difference Neural Representation for Videos | [![GitHub Page](https://img.shields.io/badge/GitHub-Page-159957.svg)](https://haochen-rye.github.io/HNeRV/) <br /> [![GitHub](https://img.shields.io/github/stars/haochen-rye/HNeRV?style=flat)](https://github.com/haochen-rye/HNeRV) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Zhao_DNeRV_Modeling_Inherent_Dynamics_via_Difference_Neural_Representation_for_Videos_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2304.06544-b31b1b.svg)](http://arxiv.org/abs/2304.06544) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=v7_fqRxiKEI) |
| Exploring Discontinuity for Video Frame Interpolation <br/> [![CVPR - Highlight](https://img.shields.io/badge/CVPR-Highlight-FFFF00)]() | [![GitHub](https://img.shields.io/github/stars/pandatimo/Exploring-Discontinuity-for-VFI?style=flat)](https://github.com/pandatimo/Exploring-Discontinuity-for-VFI) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Lee_Exploring_Discontinuity_for_Video_Frame_Interpolation_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2202.07291-b31b1b.svg)](http://arxiv.org/abs/2202.07291) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=uaKJtD-2KZc) |
| Neural Video Compression with Diverse Contexts | | | |
| FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation | | | |
| OPE-SR: Orthogonal Position Encoding for Designing a Parameter-Free Upsampling Module in Arbitrary-Scale Image Super-Resolution | | | |
| Context-based Trit-Plane Coding for Progressive Image Compression | | | |
| All-in-One Image Restoration for Unknown Degradations using Adaptive Discriminative Filters for Specific Degradations | | | |
| Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization | | | |
| Neural Video Compression With Diverse Contexts | [![GitHub](https://img.shields.io/github/stars/microsoft/DCVC?style=flat)](https://github.com/microsoft/DCVC) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Li_Neural_Video_Compression_With_Diverse_Contexts_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2302.14402-b31b1b.svg)](http://arxiv.org/abs/2302.14402) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=s8PSvl5FbWQ) |
| FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation | [![GitHub](https://img.shields.io/github/stars/XiaoyuShi97/FlowFormerPlusPlus?style=flat)](https://github.com/XiaoyuShi97/FlowFormerPlusPlus) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Shi_FlowFormer_Masked_Cost_Volume_Autoencoding_for_Pretraining_Optical_Flow_Estimation_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.01237-b31b1b.svg)](https://arxiv.org/abs/2303.01237) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=-XZi1HT0Y7o) |
| OPE-SR: Orthogonal Position Encoding for Designing a Parameter-Free Upsampling Module in Arbitrary-Scale Image Super-Resolution| :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Song_OPE-SR_Orthogonal_Position_Encoding_for_Designing_a_Parameter-Free_Upsampling_Module_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.01091-b31b1b.svg)](https://arxiv.org/abs/2303.01091) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=OqoiHUdZ3O0) |
| Context-Based Trit-Plane Coding for Progressive Image Compression | [![GitHub](https://img.shields.io/github/stars/seungminjeon-github/CTC?style=flat)](https://github.com/seungminjeon-github/CTC) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Jeon_Context-Based_Trit-Plane_Coding_for_Progressive_Image_Compression_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.05715-b31b1b.svg)](http://arxiv.org/abs/2303.05715) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=p1_UW8cge7g) |
| All-in-One Image Restoration for Unknown Degradations Using Adaptive Discriminative Filters for Specific Degradations| :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Park_All-in-One_Image_Restoration_for_Unknown_Degradations_Using_Adaptive_Discriminative_Filters_CVPR_2023_paper.pdf) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=xn3EpFsZ_hQ) |
| Learning To Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Qin_Learning_To_Exploit_the_Sequence-Specific_Prior_Knowledge_for_Image_Processing_CVPR_2023_paper.pdf) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=Oh-kgpe-S_Y) |
| Nighttime Smartphone Reflective Flare Removal using Optical Center Symmetry Prior | | | |
| Enhancing Deformable Local Features by Jointly Learning to Detect and Describe Keypoints | | | |
| Real-Time Controllable Denoising for Image and Video | | | |
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