mlsanityData to 7 Oct 2026

Learning Texture Transformer Network for Image Super-Resolution

arXiv 2006.04139 ↗First posted 7 Jun 2020cs.CVcited by 346

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Cited by 23 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We study on image super-resolution (SR), which aims to recover realistic textures from a low-resolution (LR) image. Recent progress has been made by taking high-resolution images as references (Ref), so that relevant textures can be transferred to LR images. However, existing SR approaches neglect to use attention mechanisms to transfer high-resolution (HR) textures from Ref images, which limits these approaches in challenging cases. In this paper, we propose a novel Texture Transformer Network for Image Super-Resolution (TTSR), in which the LR and Ref images are formulated as queries and keys in a transformer, respectively. TTSR consists of four closely-related modules optimized for image generation tasks, including a learnable texture extractor by DNN, a relevance embedding module, a hard-attention module for texture transfer, and a soft-attention module for texture synthesis. Such a design encourages joint feature learning across LR and Ref images, in which deep feature correspondences can be discovered by attention, and thus accurate texture features can be transferred. The proposed texture transformer can be further stacked in a cross-scale way, which enables texture recovery from different levels (e.g., from 1x to 4x magnification). Extensive experiments show that TTSR achieves significant improvements over state-of-the-art approaches on both quantitative and qualitative evaluations.

Key facts. Cited by 346 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jun 2020.

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Citing papers per year: 2021: 86; 2022: 89; 2023: 65; 2024: 48; 2025: 33; 2026: 25.

346 papers.

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  1. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  2. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,096
  3. 2021Transformers in Vision: A Surveycited by 1,009
  4. 2021CvT: Introducing Convolutions to Vision Transformerscited by 946
  5. 2021Uformer: A General U-Shaped Transformer for Image Restorationcited by 864
  6. 2021Twins: Revisiting the Design of Spatial Attention in Vision Transformerscited by 565
  7. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 549
  8. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolutioncited by 486
  9. 2021VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Textcited by 427
  10. 2021Remote Sensing Image Change Detection with Transformerscited by 305
  11. 2021TransVG: End-to-End Visual Grounding with Transformerscited by 269
  12. 2021Incorporating Convolution Designs into Visual Transformerscited by 248
38 more
  1. 2022MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generationcited by 225
  2. 2021Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encodingcited by 207
  3. 2023Learning A Sparse Transformer Network for Effective Image Derainingcited by 204
  4. 2021Chasing Sparsity in Vision Transformers: An End-to-End Explorationcited by 181
  5. 2021SPViT: Enabling Faster Vision Transformers via Soft Token Pruningcited by 165
  6. 2021TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Upcited by 162
  7. 2021Transformer for Single Image Super-Resolutioncited by 150
  8. 2022A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstructioncited by 150
  9. 2021Efficient Self-supervised Vision Transformers for Representation Learningcited by 149
  10. 2021All Tokens Matter: Token Labeling for Training Better Vision Transformerscited by 144
  11. 2022Stripformer: Strip Transformer for Fast Image Deblurringcited by 139
  12. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 139
  13. 2021End-to-End Dense Video Captioning with Parallel Decodingcited by 133
  14. 2021Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimationcited by 122
  15. 2021Video Super-Resolution Transformercited by 120
  16. 2023PromptIR: Prompting for All-in-One Blind Image Restorationcited by 113
  17. 2022Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priorscited by 98
  18. 2022M3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-designcited by 97
  19. 2021NeRF-SR: High-Quality Neural Radiance Fields using Supersamplingcited by 95
  20. 2021Aggregated Contextual Transformations for High-Resolution Image Inpaintingcited by 89
  21. 2022RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairscited by 85
  22. 2022Accurate Image Restoration with Attention Retractable Transformercited by 85
  23. 2021MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolutioncited by 79
  24. 2022Unified Visual Transformer Compressioncited by 79
  25. 2022High-resolution Iterative Feedback Network for Camouflaged Object Detectioncited by 78
  26. 2021Progressively Normalized Self-Attention Network for Video Polyp Segmentationcited by 75
  27. 2022Improving Vision Transformers by Revisiting High-frequency Componentscited by 75
  28. 2021M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformerscited by 74
  29. 2021HiFT: Hierarchical Feature Transformer for Aerial Trackingcited by 72
  30. 2022Any-resolution Training for High-resolution Image Synthesiscited by 72
  31. 2024Complexity Experts are Task-Discriminative Learners for Any Image Restorationcited by 72
  32. 2022Rethinking Alignment in Video Super-Resolution Transformerscited by 71
  33. 2021Robust Reference-based Super-Resolution via C2-Matchingcited by 68
  34. 2023CoSeR: Bridging Image and Language for Cognitive Super-Resolutioncited by 66
  35. 2022Learning Trajectory-Aware Transformer for Video Super-Resolutioncited by 61
  36. 2021Task Transformer Network for Joint MRI Reconstruction and Super-Resolutioncited by 58
  37. 2022Where in the World is this Image? Transformer-based Geo-localization in the Wildcited by 58
  38. 2024Zero-Reference Low-Light Enhancement via Physical Quadruple Priorscited by 58

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