% Key papers for CNN and transformer SR architectures (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_photo_12531,
  title = {{Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_residual_13525,
  title = {{Residual Dense Network for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zhang_Residual_Dense_Network_CVPR_2018_paper.html},
}

@inproceedings{cvpr2016_deeply_11487,
  title = {{Deeply-Recursive Convolutional Network for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2017_deep_12155,
  title = {{Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2017_image_12344,
  title = {{Image Super-Resolution via Deep Recursive Residual Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_deep_12955,
  title = {{Deep Back-Projection Networks for Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Haris_Deep_Back-Projection_Networks_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_recovering_13510,
  title = {{Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Recovering_Realistic_Texture_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_feedback_14209,
  title = {{Feedback Network for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_deep_15379,
  title = {{Deep Unfolding Network for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_residual_16111,
  title = {{Residual Feature Aggregation Network for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2019_meta_14512,
  title = {{Meta-SR: A Magnification-Arbitrary Network for Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_structure_16295,
  title = {{Structure-Preserving Super Resolution With Gradient Guidance}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_image_15674,
  title = {{Image Super-Resolution With Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_interpreting_17198,
  title = {{Interpreting Super-Resolution Networks With Local Attribution Maps}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_exploring_16980,
  title = {{Exploring Sparsity in Image Super-Resolution for Efficient Inference}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_ode_14584,
  title = {{ODE-Inspired Network Design for Single Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_glean_17057,
  title = {{GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2023_n_21636,
  title = {{N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22675},
}

@inproceedings{cvpr2022_details_18652,
  title = {{Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_classsr_16702,
  title = {{ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2024_transcending_25081,
  title = {{Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31295},
}

@inproceedings{cvpr2024_sed_24758,
  title = {{SeD: Semantic-Aware Discriminator for Image Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31331},
}

@inproceedings{aaai2024_osffnet_6805,
  title = {{OSFFNet: Omni-Stage Feature Fusion Network for Lightweight Image Super-Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28377},
}

@inproceedings{cvpr2024_image_23753,
  title = {{Image Processing GNN: Breaking Rigidity in Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30684},
}

@inproceedings{aaai2024_uncertainty_7679,
  title = {{Uncertainty-Aware GAN for Single Image Super Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28201},
}

@inproceedings{aaai2024_mftn_6576,
  title = {{MFTN: Multi-Level Feature Transfer Network Based on MRI-Transformer for MR Image Super-resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28011},
}

@inproceedings{aaai2024_iterative_6360,
  title = {{Iterative Token Evaluation and Refinement for Real-World Super-resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27861},
}

@inproceedings{cvpr2025_exploring_26190,
  title = {{Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality Assessment}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34754},
}

@inproceedings{aaai2026_cd_100690,
  title = {{CD-DPE: Dual-Prompt Expert Network Based on Convolutional Dictionary Feature Decoupling for Multi-Contrast MRI Super-Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/42430},
}

@inproceedings{aaai2026_mixture_100729,
  title = {{Mixture of Ranks with Degradation-Aware Routing for One-Step Real-World Image Super-Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/42469},
}

@inproceedings{aaai2026_trt_104914,
  title = {{TRT: Harnessing Tensor Ring Transformer for Hyperspectral Image Super-Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38103},
}

@inproceedings{aaai2024_post_6970,
  title = {{Post-trained Convolution Networks for Single Image Super-resolution (Abstract Reprint)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30614},
}

@inproceedings{icml2024_exploring_43261,
  title = {{Exploring the Low-Pass Filtering Behavior in Image Super-Resolution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35191},
}

@inproceedings{cvpr2026_ucan_99585,
  title = {{UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Tan_UCAN_Unified_Convolutional_Attention_Network_for_Expansive_Receptive_Fields_in_CVPR_2026_paper.html},
}

@inproceedings{icml2026_enhanced_54444,
  title = {{Enhanced Latent-Space Adversarial Training for Super-Resolution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=oyTUP62M7s},
}