mlsanityData to 7 Oct 2026

Hypernetwork functional image representation

arXiv 1902.10404 ↗First posted 27 Feb 2019cs.LG cs.CV stat.MLcited by 65

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Abstract (arXiv)

Motivated by the human way of memorizing images we introduce their functional representation, where an image is represented by a neural network. For this purpose, we construct a hypernetwork which takes an image and returns weights to the target network, which maps point from the plane (representing positions of the pixel) into its corresponding color in the image. Since the obtained representation is continuous, one can easily inspect the image at various resolutions and perform on it arbitrary continuous operations. Moreover, by inspecting interpolations we show that such representation has some properties characteristic to generative models. To evaluate the proposed mechanism experimentally, we apply it to image super-resolution problem. Despite using a single model for various scaling factors, we obtained results comparable to existing super-resolution methods.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2019.

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Citing papers per year: 2021: 11; 2022: 10; 2023: 16; 2024: 11; 2025: 10; 2026: 7.

65 papers.

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  1. 2021Personalized Federated Learning using Hypernetworkscited by 210
  2. 2021Modulated Periodic Activations for Generalizable Local Functional Representationscited by 140
  3. 2023Similarity of Neural Network Models: A Survey of Functional and Representational Measurescited by 128
  4. 2023A Brief Review of Hypernetworks in Deep Learningcited by 102
  5. 2021A Structured Dictionary Perspective on Implicit Neural Representationscited by 100
  6. 2021HyperMorph: Amortized Hyperparameter Learning for Image Registrationcited by 84
  7. 2023CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representationscited by 67
  8. 2021UltraSR: Spatial Encoding is a Missing Key for Implicit Image Function-based Arbitrary-Scale Super-Resolutioncited by 56
  9. 2023Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolutioncited by 51
  10. 2023Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictionscited by 38
  11. 2024Improved Implicit Neural Representation with Fourier Reparameterized Trainingcited by 36
  12. 2022Learning the Effect of Registration Hyperparameters with HyperMorphcited by 35
38 more
  1. 2023INCODE: Implicit Neural Conditioning with Prior Knowledge Embeddingscited by 31
  2. 2022Implicit Full Waveform Inversion with Deep Neural Representationcited by 26
  3. 2021Block Contextual MDPs for Continual Learningcited by 25
  4. 2023HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetworkcited by 25
  5. 2023HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillationcited by 19
  6. 2023Principled Weight Initialization for Hypernetworkscited by 19
  7. 2021HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworkscited by 18
  8. 2025Pareto Set Learning for Multi-Objective Reinforcement Learningcited by 18
  9. 2024HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolutioncited by 17
  10. 2025Instant GaussianImage: A Generalizable and Self-Adaptive Image Representation via 2D Gaussian Splattingcited by 17
  11. 2022Example-based Hypernetworks for Out-of-Distribution Generalizationcited by 16
  12. 2022TINC: Tree-structured Implicit Neural Compressioncited by 14
  13. 2024FreSh: Frequency Shifting for Accelerated Neural Representation Learningcited by 14
  14. 2022SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Datacited by 13
  15. 2021HyperPocket: Generative Point Cloud Completioncited by 12
  16. 2022HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworkscited by 12
  17. 2024HAIR: Hypernetworks-based All-in-One Image Restorationcited by 12
  18. 2024MiraGe: Editable 2D Images using Gaussian Splattingcited by 12
  19. 2023Hypernetworks build Implicit Neural Representations of Soundscited by 11
  20. 2021Hyper-Convolution Networks for Biomedical Image Segmentationcited by 10
  21. 2023HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasetscited by 10
  22. 2023Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisationcited by 10
  23. 2023HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendationcited by 10
  24. 2021Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworkscited by 9
  25. 2024Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generationcited by 9
  26. 2024VeGaS: Video Gaussian Splattingcited by 9
  27. 2024Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representationscited by 8
  28. 2022Computing Multiple Image Reconstructions with a Single Hypernetworkcited by 7
  29. 2025MedFuncta: A Unified Framework for Learning Efficient Medical Neural Fieldscited by 6
  30. 2021Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labelscited by 4
  31. 2022Multi-Curve Translator for High-Resolution Photorealistic Image Translationcited by 3
  32. 2023Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image Representationcited by 3
  33. 2022Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchiescited by 2
  34. 2024FedSheafHN: Personalized Federated Learning on Graph-structured Datacited by 2
  35. 2025LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encodingcited by 2
  36. 2022Hyper-Convolutions via Implicit Kernels for Medical Imagingcited by 1
  37. 2023DrasCLR: A Self-supervised Framework of Learning Disease-related and Anatomy-specific Representation for 3D Medical Imagescited by 1
  38. 2024Implicit Neural Representation For Accurate CFD Flow Field Predictioncited by 1

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