mlsanityData to 7 Oct 2026

Adversarial Generation of Continuous Images

arXiv 2011.12026 ↗First posted 24 Nov 2020cs.CV cs.AI cs.LGcited by 135

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Abstract (arXiv)

In most existing learning systems, images are typically viewed as 2D pixel arrays. However, in another paradigm gaining popularity, a 2D image is represented as an implicit neural representation (INR) - an MLP that predicts an RGB pixel value given its (x,y) coordinate. In this paper, we propose two novel architectural techniques for building INR-based image decoders: factorized multiplicative modulation and multi-scale INRs, and use them to build a state-of-the-art continuous image GAN. Previous attempts to adapt INRs for image generation were limited to MNIST-like datasets and do not scale to complex real-world data. Our proposed INR-GAN architecture improves the performance of continuous image generators by several times, greatly reducing the gap between continuous image GANs and pixel-based ones. Apart from that, we explore several exciting properties of the INR-based decoders, like out-of-the-box superresolution, meaningful image-space interpolation, accelerated inference of low-resolution images, an ability to extrapolate outside of image boundaries, and strong geometric prior. The project page is located at https://universome.github.io/inr-gan.

Key facts. Cited by 135 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Nov 2020.

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Citing papers per year: 2021: 21; 2022: 38; 2023: 30; 2024: 25; 2025: 14; 2026: 7.

135 papers.

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  1. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  2. 2021Neural Fields in Visual Computing and Beyondcited by 539
  3. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  4. 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
  5. 2022Generating Videos with Dynamics-aware Implicit Generative Adversarial Networkscited by 186
  6. 2022From data to functa: Your data point is a function and you can treat it like onecited by 183
  7. 2021Implicit Neural Representations for Image Compressioncited by 161
  8. 2021StyleSwin: Transformer-based GAN for High-resolution Image Generationcited by 152
  9. 2021CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesiscited by 149
  10. 2023Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Modelscited by 131
  11. 2022EpiGRAF: Rethinking training of 3D GANscited by 108
  12. 2022VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolutioncited by 101
38 more
  1. 2023DiffCollage: Parallel Generation of Large Content with Diffusion Modelscited by 100
  2. 2021Generative Models as Distributions of Functionscited by 89
  3. 2022COIN++: Neural Compression Across Modalitiescited by 81
  4. 2023Score-based Diffusion Models in Function Spacecited by 80
  5. 2022Transformers as Meta-Learners for Implicit Neural Representationscited by 79
  6. 2022VIDM: Video Implicit Diffusion Modelscited by 78
  7. 2025PixNerd: Pixel Neural Field Diffusioncited by 75
  8. 2022Any-resolution Training for High-resolution Image Synthesiscited by 72
  9. 2021Aligning Latent and Image Spaces to Connect the Unconnectablecited by 70
  10. 2021CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assemblycited by 62
  11. 2021Geometry-Consistent Neural Shape Representation with Implicit Displacement Fieldscited by 60
  12. 2021On the Frequency Bias of Generative Modelscited by 60
  13. 2021Improved Transformer for High-Resolution GANscited by 59
  14. 2021SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editingcited by 58
  15. 2023AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesiscited by 49
  16. 2021Meta-Learning Sparse Implicit Neural Representationscited by 48
  17. 2022FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videoscited by 46
  18. 2021Learning Signal-Agnostic Manifolds of Neural Fieldscited by 45
  19. 2022Low-Rank Tensor Function Representation for Multi-Dimensional Data Recoverycited by 45
  20. 2023Task-Oriented Human-Object Interactions Generation with Implicit Neural Representationscited by 41
  21. 2023MoStGAN-V: Video Generation with Temporal Motion Stylescited by 37
  22. 2021SphereSR: 360deg Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representationcited by 33
  23. 2022Generalised Implicit Neural Representationscited by 31
  24. 2022Scalable Neural Video Representations with Learnable Positional Featurescited by 29
  25. 2022Neural Fourier Filter Bankcited by 29
  26. 2024Boosting Neural Representations for Videos with a Conditional Decodercited by 29
  27. 2024Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decodercited by 25
  28. 2022HyperTime: Implicit Neural Representation for Time Seriescited by 24
  29. 2022PV3D: A 3D Generative Model for Portrait Video Generationcited by 23
  30. 2023Modality-Agnostic Variational Compression of Implicit Neural Representationscited by 22
  31. 2023Variational Autoencoding Neural Operatorscited by 22
  32. 2024Latent Modulated Function for Computational Optimal Continuous Image Representationcited by 21
  33. 2022Arbitrary-Scale Image Synthesiscited by 20
  34. 2022PINs: Progressive Implicit Networks for Multi-Scale Neural Representationscited by 19
  35. 2023Dense Pixel-to-Pixel Harmonization via Continuous Image Representationcited by 19
  36. 2023HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillationcited by 19
  37. 2021Neural Image Representations for Multi-Image Fusion and Layer Separationcited by 18
  38. 2022Generative Range Imaging for Learning Scene Priors of 3D LiDAR Datacited by 18

50 most cited of 135 All 135 (JSON)