mlsanityData to 7 Oct 2026

Deep Back-Projection Networks For Super-Resolution

arXiv 1803.02735 ↗First posted 7 Mar 2018cs.CVcited by 224

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Cited by 21 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output. However, this approach does not fully address the mutual dependencies of low- and high-resolution images. We propose Deep Back-Projection Networks (DBPN), that exploit iterative up- and down-sampling layers, providing an error feedback mechanism for projection errors at each stage. We construct mutually-connected up- and down-sampling stages each of which represents different types of image degradation and high-resolution components. We show that extending this idea to allow concatenation of features across up- and down-sampling stages (Dense DBPN) allows us to reconstruct further improve super-resolution, yielding superior results and in particular establishing new state of the art results for large scaling factors such as 8x across multiple data sets.

Key facts. Cited by 224 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Mar 2018.

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Citing papers per year: 2021: 65; 2022: 51; 2023: 43; 2024: 35; 2025: 21; 2026: 9.

224 papers.

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  1. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  2. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 961
  3. 2022Denoising Diffusion Restoration Modelscited by 951
  4. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shiftingcited by 360
  5. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancementcited by 198
  6. 2021SNIPS: Solving Noisy Inverse Problems Stochasticallycited by 191
  7. 2021Unsupervised Degradation Representation Learning for Blind Super-Resolutioncited by 177
  8. 2022VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolutioncited by 174
  9. 2023Efficient and Explicit Modelling of Image Hierarchies for Image Restorationcited by 145
  10. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagerycited by 130
  11. 2023Dual Aggregation Transformer for Image Super-Resolutioncited by 124
  12. 2021R2RNet: Low-light Image Enhancement via Real-low to Real-normal Networkcited by 106
38 more
  1. 2024Pixel-level and Semantic-level Adjustable Super-resolution: A Dual-LoRA Approachcited by 93
  2. 2021LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyondcited by 88
  3. 2022Accurate Image Restoration with Attention Retractable Transformercited by 85
  4. 2022High-resolution Iterative Feedback Network for Camouflaged Object Detectioncited by 78
  5. 2021Fourier Space Losses for Efficient Perceptual Image Super-Resolutioncited by 72
  6. 2022Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restorationcited by 72
  7. 2021Real-World Single Image Super-Resolution: A Brief Reviewcited by 65
  8. 2021Burst Image Restoration and Enhancementcited by 64
  9. 2024Efficient Diffusion Model for Image Restoration by Residual Shiftingcited by 64
  10. 2023Learning to Upsample by Learning to Samplecited by 57
  11. 2021NTIRE 2021 Challenge on Image Deblurringcited by 49
  12. 2022Deep Constrained Least Squares for Blind Image Super-Resolutioncited by 47
  13. 2021Image Inpainting by End-to-End Cascaded Refinement with Mask Awarenesscited by 35
  14. 2021SphereSR: 360deg Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representationcited by 33
  15. 2021Blind Image Super-Resolution via Contrastive Representation Learningcited by 32
  16. 2022Revisiting RCAN: Improved Training for Image Super-Resolutioncited by 32
  17. 2022BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignmentcited by 32
  18. 2023Burstormer: Burst Image Restoration and Enhancement Transformercited by 32
  19. 2021Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolutioncited by 30
  20. 2021Best-Buddy GANs for Highly Detailed Image Super-Resolutioncited by 30
  21. 2021Omniscient Video Super-Resolutioncited by 30
  22. 2021A Practical Contrastive Learning Framework for Single-Image Super-Resolutioncited by 30
  23. 2021Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolutioncited by 29
  24. 2021COMISR: Compression-Informed Video Super-Resolutioncited by 26
  25. 2021Finding Discriminative Filters for Specific Degradations in Blind Super-Resolutioncited by 26
  26. 2024SeD: Semantic-Aware Discriminator for Image Super-Resolutioncited by 26
  27. 2022Efficient Non-Local Contrastive Attention for Image Super-Resolutioncited by 25
  28. 2022IFQA: Interpretable Face Quality Assessmentcited by 24
  29. 2021A Comprehensive Review of Deep Learning-based Single Image Super-resolutioncited by 23
  30. 2022AnimeSR: Learning Real-World Super-Resolution Models for Animation Videoscited by 23
  31. 2024DVMSR: Distillated Vision Mamba for Efficient Super-Resolutioncited by 23
  32. 2021NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Resultscited by 22
  33. 2022A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Boundscited by 22
  34. 2023Accelerating Diffusion Models for Inverse Problems through Shortcut Samplingcited by 21
  35. 2021A Two-Stage Attentive Network for Single Image Super-Resolutioncited by 20
  36. 2021Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesiscited by 20
  37. 2022Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networkscited by 20
  38. 2022Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modelingcited by 20

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