mlsanityData to 7 Oct 2026

Implicit Transformer Network for Screen Content Image Continuous Super-Resolution

arXiv 2112.06174 ↗First posted 12 Dec 2021cs.CV cs.MMcited by 46

Not on the map. Why?

Abstract (arXiv)

Nowadays, there is an explosive growth of screen contents due to the wide application of screen sharing, remote cooperation, and online education. To match the limited terminal bandwidth, high-resolution (HR) screen contents may be downsampled and compressed. At the receiver side, the super-resolution (SR) of low-resolution (LR) screen content images (SCIs) is highly demanded by the HR display or by the users to zoom in for detail observation. However, image SR methods mostly designed for natural images do not generalize well for SCIs due to the very different image characteristics as well as the requirement of SCI browsing at arbitrary scales. To this end, we propose a novel Implicit Transformer Super-Resolution Network (ITSRN) for SCISR. For high-quality continuous SR at arbitrary ratios, pixel values at query coordinates are inferred from image features at key coordinates by the proposed implicit transformer and an implicit position encoding scheme is proposed to aggregate similar neighboring pixel values to the query one. We construct benchmark SCI1K and SCI1K-compression datasets with LR and HR SCI pairs. Extensive experiments show that the proposed ITSRN significantly outperforms several competitive continuous and discrete SR methods for both compressed and uncompressed SCIs.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). Builds on 26 of its 41 references that are in the map. First posted on arXiv 12 Dec 2021.

Builds on

26 of 41 references.

References · 26

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  6. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  7. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  8. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  9. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  10. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,543
  11. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,256
  12. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
14 more
  1. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 902
  2. 2018Residual Dense Network for Image Super-Resolutioncited by 796
  3. 2020Convolutional Occupancy Networkscited by 760
  4. 2017Convolutional Sequence to Sequence Learningcited by 550
  5. 2020Learning Continuous Image Representation with Local Implicit Image Functioncited by 550
  6. 2017Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolutioncited by 452
  7. 2019SAL: Sign Agnostic Learning of Shapes from Raw Datacited by 389
  8. 2020Learning Texture Transformer Network for Image Super-Resolutioncited by 346
  9. 2019Meta-SR: A Magnification-Arbitrary Network for Super-Resolutioncited by 180
  10. 2020DeRF: Decomposed Radiance Fieldscited by 163
  11. 2019Feedback Network for Image Super-Resolutioncited by 155
  12. 2019Image Super-Resolution by Neural Texture Transfercited by 119
  13. 2020Cross-Scale Internal Graph Neural Network for Image Super-Resolutioncited by 94
  14. 2019Densely Residual Laplacian Super-Resolutioncited by 57

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 6; 2023: 4; 2024: 17; 2025: 9; 2026: 9.

46 papers.

Sort:

By area:

  1. 2022CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolutioncited by 69
  2. 2023Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolutioncited by 51
  3. 2023Super-Resolution Neural Operatorcited by 48
  4. 2025Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modelingcited by 47
  5. 2022Low-Rank Tensor Function Representation for Multi-Dimensional Data Recoverycited by 45
  6. 2023Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolutioncited by 34
  7. 2022Masked Lip-Sync Prediction by Audio-Visual Contextual Exploitation in Transformerscited by 33
  8. 2022Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advancescited by 21
  9. 2024Latent Modulated Function for Computational Optimal Continuous Image Representationcited by 21
  10. 2025Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-Resolutioncited by 21
  11. 2024CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Datacited by 15
  12. 2022Learning Local Implicit Fourier Representation for Image Warpingcited by 14
34 more
  1. 2024Revisiting Nonlocal Self-Similarity from Continuous Representationcited by 14
  2. 2024Image Neural Field Diffusion Modelscited by 13
  3. 2024S3Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Modelcited by 12
  4. 2025PICD: Versatile Perceptual Image Compression with Diffusion Renderingcited by 10
  5. 2024Boosting Flow-based Generative Super-Resolution Models via Learned Priorcited by 7
  6. 2024Exploring the Low-Pass Filtering Behavior in Image Super-Resolutioncited by 7
  7. 2021Continuous Spectral Reconstruction from RGB Images via Implicit Neural Representationcited by 3
  8. 2024Learning Dual-Level Deformable Implicit Representation for Real-World Scale Arbitrary Super-Resolutioncited by 3
  9. 2025StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representationcited by 3
  10. 2026SGI: Structured 2D Gaussians for Efficient and Compact Large Image Representationcited by 3
  11. 2022ITSRN++: Stronger and Better Implicit Transformer Network for Continuous Screen Content Image Super-Resolutioncited by 2
  12. 2023SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolutioncited by 2
  13. 2024PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolutioncited by 2
  14. 2024An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolutioncited by 1
  15. 2024DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusioncited by 1
  16. 2024LeRF: Learning Resampling Function for Adaptive and Efficient Image Interpolationcited by 1
  17. 2024Few-Shot Domain Adaptation for Learned Image Compressioncited by 1
  18. 2024Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Datacited by 1
  19. 2024An Information-Theoretic Regularizer for Lossy Neural Image Compressioncited by 1
  20. 2025Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolutioncited by 1
  21. 2025Low-Rank Tensor Recovery via Variational Schatten-p Quasi-Norm and Jacobian Regularizationcited by 1
  22. 2025Towards Robust and Generalizable Continuous Space-Time Video Super-Resolution with Eventscited by 1
  23. 2026G-ZAP: A Generalizable Zero-Shot Framework for Arbitrary-Scale Pansharpeningcited by 1
  24. 2024Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolutioncited by 0
  25. 2024Adaptive Resolution Residual Networks -- Generalizing Across Resolutions Easily and Efficientlycited by 0
  26. 2025Unwarping Screen Content Images via Structure-texture Enhancement Network and Transformation Self-estimationcited by 0
  27. 2025JPEG Processing Neural Operator for Backward-Compatible Codingcited by 0
  28. 2026Station2Radar: query conditioned gaussian splatting for precipitation fieldcited by 0
  29. 2026Frequency Decoupled Framework for Screen Content Image Super-Resolutioncited by 0
  30. 2026Fidelity- and Perception-Aware Local Implicit Attention for Arbitrary-Scale Image Super-Resolutioncited by 0
  31. 2026Adaptive Densification for High-Fidelity and Efficient Sparse Gaussian Splatting in Arbitrary-Scale Super-Resolutioncited by 0
  32. 2026Resonant Brane Splatting for Arbitrary-Scale Super-Resolutioncited by 0
  33. 2026PixelSR: Efficient Screen Content Super-Resolution via Pixel Classificationcited by 0
  34. 2026Towards Adaptive Super-Resolution and Quality Assessment via Test-Time Adaptationcited by 0