mlsanityData to 14 Oct 2026

Transformer for Single Image Super-Resolution

arXiv 2108.11084 ↗First posted 25 Aug 2021cs.CVcited by 150

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Abstract (arXiv)

Single image super-resolution (SISR) has witnessed great strides with the development of deep learning. However, most existing studies focus on building more complex networks with a massive number of layers. Recently, more and more researchers start to explore the application of Transformer in computer vision tasks. However, the heavy computational cost and high GPU memory occupation of the vision Transformer cannot be ignored. In this paper, we propose a novel Efficient Super-Resolution Transformer (ESRT) for SISR. ESRT is a hybrid model, which consists of a Lightweight CNN Backbone (LCB) and a Lightweight Transformer Backbone (LTB). Among them, LCB can dynamically adjust the size of the feature map to extract deep features with a low computational cost. LTB is composed of a series of Efficient Transformers (ET), which occupies a small GPU memory occupation, thanks to the specially designed Efficient Multi-Head Attention (EMHA). Extensive experiments show that ESRT achieves competitive results with low computational costs. Compared with the original Transformer which occupies 16,057M GPU memory, ESRT only occupies 4,191M GPU memory. All codes are available at https://github.com/luissen/ESRT.

Key facts. Cited by 150 papers in the map (data through 14 Oct 2026). Builds on 30 of its 45 references that are in the map. First posted on arXiv 25 Aug 2021.

Builds on

30 of 45 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2020End-to-End Object Detection with Transformerscited by 7,414
  6. 2016Layer Normalizationcited by 5,669
  7. 2017Squeeze-and-Excitation Networkscited by 4,789
  8. 2020Training data-efficient image transformers & distillation through attentioncited by 4,586
  9. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  10. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  11. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,552
  12. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,264
18 more
  1. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,224
  2. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,204
  3. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 903
  4. 2020Pre-Trained Image Processing Transformercited by 893
  5. 2018Residual Dense Network for Image Super-Resolutioncited by 799
  6. 2019Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Modelcited by 403
  7. 2020Learning Texture Transformer Network for Image Super-Resolutioncited by 347
  8. 2015Deeply-Recursive Convolutional Network for Image Super-Resolutioncited by 317
  9. 2018Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Networkcited by 264
  10. 2017MemNet: A Persistent Memory Network for Image Restorationcited by 244
  11. 2017Learning a Single Convolutional Super-Resolution Network for Multiple Degradationscited by 228
  12. 2021LocalViT: Analyzing Locality in Vision Transformerscited by 228
  13. 2019Lightweight Image Super-Resolution with Information Multi-distillation Networkcited by 227
  14. 2017Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networkscited by 138
  15. 2020Residual Feature Distillation Network for Lightweight Image Super-Resolutioncited by 122
  16. 2018Fast and Accurate Single Image Super-Resolution via Information Distillation Networkcited by 121
  17. 2020Building a Manga Dataset "Manga109" with Annotations for Multimedia Applicationscited by 38
  18. 2020Multi-Attention Based Ultra Lightweight Image Super-Resolutioncited by 23

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 11; 2023: 38; 2024: 42; 2025: 44; 2026: 14.

150 papers.

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  1. 2022A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstructioncited by 152
  2. 2024FeatUp: A Model-Agnostic Framework for Features at Any Resolutioncited by 116
  3. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 109
  4. 2023Omni Aggregation Networks for Lightweight Image Super-Resolutioncited by 62
  5. 2023Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolutioncited by 57
  6. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Modelcited by 47
  7. 2023Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolutioncited by 33
  8. 2024CAMixerSR: Only Details Need More "Attention"cited by 30
  9. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  10. 2024QMambaBSR: Burst Image Super-Resolution with Query State Space Modelcited by 27
  11. 2024SeD: Semantic-Aware Discriminator for Image Super-Resolutioncited by 26
  12. 2025Progressive Focused Transformer for Single Image Super-Resolutioncited by 25
38 more
  1. 2024See More Details: Efficient Image Super-Resolution by Experts Miningcited by 23
  2. 2022Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformercited by 22
  3. 2021A Systematic Survey of Deep Learning-based Single-Image Super-Resolutioncited by 19
  4. 2022CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolutioncited by 19
  5. 2023Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function Spacecited by 18
  6. 2023ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolutioncited by 18
  7. 2024MTKD: Multi-Teacher Knowledge Distillation for Image Super-Resolutioncited by 17
  8. 2024Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolutioncited by 16
  9. 2025CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolutioncited by 16
  10. 2024Wind speed super-resolution and validation: from ERA5 to CERRA via diffusion modelscited by 15
  11. 2024Generating Content for HDR Deghosting from Frequency Viewcited by 14
  12. 2024MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMscited by 14
  13. 2025NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Resultscited by 14
  14. 2022Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Networkcited by 13
  15. 2024DiffFNO: Diffusion Fourier Neural Operatorcited by 13
  16. 2025Text2CT: Towards 3D CT Volume Generation from Free-text Descriptions Using Diffusion Modelcited by 13
  17. 2023Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNNcited by 12
  18. 2023TULIP: Transformer for Upsampling of LiDAR Point Cloudscited by 12
  19. 2025CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual Inferencecited by 12
  20. 2022HIPA: Hierarchical Patch Transformer for Single Image Super Resolutioncited by 11
  21. 2023High-Similarity-Pass Attention for Single Image Super-Resolutioncited by 11
  22. 2023Learning from History: Task-agnostic Model Contrastive Learning for Image Restorationcited by 11
  23. 2024CFAT: Unleashing TriangularWindows for Image Super-resolutioncited by 11
  24. 2025NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Studycited by 11
  25. 2023Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolutioncited by 10
  26. 2025ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscalingcited by 10
  27. 2023Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 imagescited by 9
  28. 2022Real-World Light Field Image Super-Resolution via Degradation Modulationcited by 8
  29. 2022Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Imagescited by 8
  30. 2023LDM3D-VR: Latent Diffusion Model for 3D VRcited by 8
  31. 2025BokehDiff: Neural Lens Blur with One-Step Diffusioncited by 8
  32. 2023NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Resultscited by 7
  33. 2024Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Methodcited by 7
  34. 2023LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformercited by 6
  35. 2023PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-Resolutioncited by 6
  36. 2023Reciprocal Attention Mixing Transformer for Lightweight Image Restorationcited by 6
  37. 2024CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Taskcited by 6
  38. 2024A Comparative Survey of Vision Transformers for Feature Extraction in Texture Analysiscited by 6

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