{"id":13444377,"url":"https://github.com/ChaofWang/Awesome-Super-Resolution","last_synced_at":"2025-03-20T18:32:28.419Z","repository":{"id":37431189,"uuid":"182422786","full_name":"ChaofWang/Awesome-Super-Resolution","owner":"ChaofWang","description":"Collect super-resolution related papers, data, 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Learning","Other Lists","Others","Awesome Computer Vision"],"sub_categories":["Uncategorized","JavaScript","TeX Lists"],"readme":"# Quick navigation\n\n- [repositories](awesome_paper_list_and_repos.md)\n- [Datasets](dataset.md)\n- [papers](#papers)\n  - [Non-DL based approach](non_dl_papers.md)\n  - [DL based approach](#DL-based-approach)\n    - [2014-2016](2014-2016_papers.md)\n    - [2017](2017_papers.md)\n    - [2018](2018_papers.md)\n    - [2019](2019_papers.md)\n    - [2020](2020_papers.md)\n    - [2021](2021_papers.md)\n    - [2022](2022_papers.md)\n    - [2023](2023_papers.md)\n\t- [2024](2024_papers.md)\n    - [2025](#2025)\n- [Super Resolution workshop papers](workshops.md)\n- [Super Resolution survey](sr_survey.md)\n\n# Awesome-Super-Resolution（in progress）\n\nCollect some super-resolution related papers, data and repositories.\n\n## papers\n\n### DL based approach\n\nNote this table is referenced from [here](https://github.com/LoSealL/VideoSuperResolution/blob/master/README.md#network-list-and-reference-updating)\n\n### 2025\nMore years papers, plase check Quick navigation\n\n| Title                  | Model                  | Published                                                    | Code                                                         | Keywords                                                     |\n| ---------------------- | ---------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |\n|CLIP-SR: Collaborative Linguistic and Image Processing for Super-Resolution|CLIP-SR | [arxiv](https://arxiv.org/abs/2412.11609) | | |\n|Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution|DPI | [AAAI25](https://arxiv.org/abs/2412.16552) |[code](https://github.com/JerryYann/DPI) | |\n|STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution|STAR | [arxiv](https://arxiv.org/abs/2501.02976) |[code](https://nju-pcalab.github.io/projects/STAR/) | |\n|StructSR: Refuse Spurious Details in Real-World Image Super-Resolution|StructSR | [AAAI25](https://arxiv.org/abs/2501.05777) |[code](https://github.com/LYCEXE/StructSR) | |\n|Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-Resolution|GSASR | [arxiv](https://arxiv.org/abs/2501.06838) |[code](https://github.com/ChrisDud0257/GSASR) | |\n|DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations|DiffVSR | [arxiv](https://arxiv.org/abs/2501.10110) |[code](https://xh9998.github.io/DiffVSR-project/) | |\n|BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-Resolution|BF-STVSR | [arxiv](https://arxiv.org/abs/2501.11043) | | |\n|Efficient Attention-Sharing Information Distillation Transformer for Lightweight Single Image Super-Resolution|ASID | [AAAI25](https://arxiv.org/abs/2501.15774) |[code](https://github.com/saturnian77/ASID) | |\n|Visual Autoregressive Modeling for Image Super-Resolution|VARSR | [arxiv](https://arxiv.org/abs/2501.18993) |[code](https://github.com/quyp2000/VARSR) | |\n|BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-Resolution|BiMaCoSR | [arxiv](https://arxiv.org/abs/2502.00333) |[code](https://github.com/Kai-Liu001/BiMaCoSR) | |\n|One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation|FluxSR | [arxiv](https://arxiv.org/abs/2502.01993) |[code](https://github.com/JianzeLi-114/FluxSR) | |\n|Fast Omni-Directional Image Super-Resolution: Adapting the Implicit Image Function with Pixel and Semantic-Wise Spherical Geometric Priors|FAOR | [AAAI25](https://arxiv.org/abs/2502.05902) |[code](https://github.com/GingaUL/FAOR) | |\n|Spatial Degradation-Aware and Temporal Consistent Diffusion Model for Compressed Video Super-Resolution|SDATC | [arxiv](https://arxiv.org/abs/2502.07381) | | |\n|CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-Resolution|CondiQuant | [arxiv](https://arxiv.org/abs/2502.15478) |[code](https://github.com/Kai-Liu001/CondiQuant) | |\n|DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution|DifIISR | [CVPR25](https://arxiv.org/abs/2503.01187) |[code](https://github.com/zirui0625/DifIISR) | |\n|AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual Learning|AutoLUT | [CVPR25](https://arxiv.org/abs/2503.01565) |[code](https://github.com/SuperKenVery/AutoLUT) | |\n|QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-Resolution|QArtSR | [arxiv](https://arxiv.org/abs/2503.05584) |[code](https://github.com/libozhu03/QArtSR) | |\n|Emulating Self-attention with Convolution for Efficient Image Super-Resolution|ESC | [arxiv](https://arxiv.org/abs/2503.06671) |[code](https://github.com/dslisleedh/ESC) | |\n|CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution|CATANet | [CVPR25](https://arxiv.org/abs/2503.06896) |[code](https://github.com/EquationWalker/CATANet) | |\n|AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution|AdaptSR | [arxiv](https://arxiv.org/abs/2503.07748) | | |\n|MegaSR: Mining Customized Semantics and Expressive Guidance for Image Super-Resolution|MegaSR | [arxiv](https://arxiv.org/abs/2503.08096) |[code](https://github.com/striveAgain/MegaSR) | |\n|Dual-domain Modulation Network for Lightweight Image Super-Resolution|DMNet | [arxiv](https://arxiv.org/abs/2503.10047) || |\n|Dynamic Attention-Guided Diffusion for Image Super-Resolution|MegaSR | [WACV 2025](https://arxiv.org/pdf/2308.07977) | | 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