mlsanityData to 14 Oct 2026

Local Texture Estimator for Implicit Representation Function

arXiv 2111.08918 ↗First posted 17 Nov 2021cs.CV eess.IVcited by 127

Not on the map. Why?

Abstract (arXiv)

Recent works with an implicit neural function shed light on representing images in arbitrary resolution. However, a standalone multi-layer perceptron shows limited performance in learning high-frequency components. In this paper, we propose a Local Texture Estimator (LTE), a dominant-frequency estimator for natural images, enabling an implicit function to capture fine details while reconstructing images in a continuous manner. When jointly trained with a deep super-resolution (SR) architecture, LTE is capable of characterizing image textures in 2D Fourier space. We show that an LTE-based neural function achieves favorable performance against existing deep SR methods within an arbitrary-scale factor. Furthermore, we demonstrate that our implementation takes the shortest running time compared to previous works.

Key facts. Cited by 127 papers in the map (data through 14 Oct 2026). Builds on 25 of its 39 references that are in the map. First posted on arXiv 17 Nov 2021.

Builds on

25 of 39 references.

References · 25

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  6. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  7. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  8. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  9. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  10. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,552
  11. 2018On the Spectral Bias of Neural Networkscited by 1,341
  12. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,264
13 more
  1. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,204
  2. 2016HyperNetworkscited by 1,027
  3. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 903
  4. 2020Pre-Trained Image Processing Transformercited by 893
  5. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  6. 2018Residual Dense Network for Image Super-Resolutioncited by 799
  7. 2020Learning Continuous Image Representation with Local Implicit Image Functioncited by 552
  8. 2020Local Implicit Grid Representations for 3D Scenescited by 373
  9. 2020Learned Initializations for Optimizing Coordinate-Based Neural Representationscited by 242
  10. 2020How Neural Networks Extrapolate: From Feedforward to Graph Neural Networkscited by 222
  11. 2019Meta-SR: A Magnification-Arbitrary Network for Super-Resolutioncited by 181
  12. 2020Learning A Single Network for Scale-Arbitrary Super-Resolutioncited by 66
  13. 2021SRWarp: Generalized Image Super-Resolution under Arbitrary Transformationcited by 27

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 8; 2023: 19; 2024: 40; 2025: 32; 2026: 28.

127 papers.

Sort:

By area:

  1. 2023Implicit Diffusion Models for Continuous Super-Resolutioncited by 218
  2. 2023Implicit Neural Representation for Cooperative Low-light Image Enhancementcited by 92
  3. 2022CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolutioncited by 70
  4. 2023AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectorscited by 64
  5. 2024Bidirectional Multi-Scale Implicit Neural Representations for Image Derainingcited by 54
  6. 2023Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolutioncited by 52
  7. 2023Super-Resolution Neural Operatorcited by 49
  8. 2025Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modelingcited by 48
  9. 2023Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolutioncited by 34
  10. 2024Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image Enhancementcited by 25
  11. 2024Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decodercited by 25
  12. 2024Latent Modulated Function for Computational Optimal Continuous Image Representationcited by 21
38 more
  1. 2024Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representationscited by 21
  2. 2025Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-Resolutioncited by 21
  3. 2022Intrinsic Neural Fields: Learning Functions on Manifoldscited by 20
  4. 2023OPE-SR: Orthogonal Position Encoding for Designing a Parameter-free Upsampling Module in Arbitrary-scale Image Super-Resolutioncited by 17
  5. 2024HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolutioncited by 17
  6. 2024CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Datacited by 15
  7. 2022Learning Local Implicit Fourier Representation for Image Warpingcited by 14
  8. 2024Image Neural Field Diffusion Modelscited by 13
  9. 2024DiffFNO: Diffusion Fourier Neural Operatorcited by 13
  10. 2024S3Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Modelcited by 12
  11. 2023Learning Continuous Exposure Value Representations for Single-Image HDR Reconstructioncited by 11
  12. 2024Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolutioncited by 11
  13. 2024Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral Image Fusioncited by 10
  14. 2024Arbitrary-Scale Video Super-Resolution with Structural and Textural Priorscited by 9
  15. 2025BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-Resolutioncited by 9
  16. 2022CUF: Continuous Upsampling Filterscited by 8
  17. 2022Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Imagescited by 8
  18. 2023Self-Supervised Scalable Deep Compressed Sensingcited by 8
  19. 2024HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion Priorcited by 8
  20. 2024Boosting Flow-based Generative Super-Resolution Models via Learned Priorcited by 7
  21. 2024JDEC: JPEG Decoding via Enhanced Continuous Cosine Coefficientscited by 7
  22. 2024Exploring the Low-Pass Filtering Behavior in Image Super-Resolutioncited by 7
  23. 2024BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical Flowcited by 7
  24. 2023Scene Matters: Model-based Deep Video Compressioncited by 6
  25. 2023Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fieldscited by 6
  26. 2024ResVR: Joint Rescaling and Viewport Rendering of Omnidirectional Imagescited by 6
  27. 2025C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scalescited by 6
  28. 2025Towards Lossless Implicit Neural Representation via Bit Plane Decompositioncited by 5
  29. 2025Emulating Self-attention with Convolution for Efficient Image Super-Resolutioncited by 5
  30. 2025Rotation Equivariant Arbitrary-scale Image Super-Resolutioncited by 5
  31. 2023Implicit Neural Image Stitchingcited by 4
  32. 2025IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolutioncited by 4
  33. 2023Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image Representationcited by 3
  34. 2023SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpaintingcited by 3
  35. 2023SAIR: Learning Semantic-aware Implicit Representationcited by 3
  36. 2024Learning Position-Aware Implicit Neural Network for Real-World Face Inpaintingcited by 3
  37. 2024Learning Dual-Level Deformable Implicit Representation for Real-World Scale Arbitrary Super-Resolutioncited by 3
  38. 2024AnySR: Realizing Image Super-Resolution as Any-Scale, Any-Resourcecited by 3

50 most cited of 127 All 127 (JSON)