mlsanityData to 14 Oct 2026

DINER: Disorder-Invariant Implicit Neural Representation

arXiv 2211.07871 ↗First posted 15 Nov 2022eess.IV cs.CVcited by 30

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Abstract (arXiv)

Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problems. However, the capacity of INR is limited by the spectral bias in the network training. In this paper, we find that such a frequency-related problem could be largely solved by re-arranging the coordinates of the input signal, for which we propose the disorder-invariant implicit neural representation (DINER) by augmenting a hash-table to a traditional INR backbone. Given discrete signals sharing the same histogram of attributes and different arrangement orders, the hash-table could project the coordinates into the same distribution for which the mapped signal can be better modeled using the subsequent INR network, leading to significantly alleviated spectral bias. Experiments not only reveal the generalization of the DINER for different INR backbones (MLP vs. SIREN) and various tasks (image/video representation, phase retrieval, and refractive index recovery) but also show the superiority over the state-of-the-art algorithms both in quality and speed.

Key facts. Cited by 30 papers in the map (data through 14 Oct 2026). Builds on 27 of its 50 references that are in the map. First posted on arXiv 15 Nov 2022.

Builds on

27 of 50 references.

References · 27

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  2. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  3. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  4. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  5. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  6. 2018On the Spectral Bias of Neural Networkscited by 1,341
  7. 2020Neural Sparse Voxel Fieldscited by 959
  8. 2021Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapescited by 426
  9. 2020Local Implicit Grid Representations for 3D Scenescited by 373
  10. 2021Advances in Neural Renderingcited by 365
  11. 2021Light Field Networks: Neural Scene Representations with Single-Evaluation Renderingcited by 332
  12. 2020Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstructioncited by 321
15 more
  1. 2021NeRV: Neural Representations for Videoscited by 256
  2. 2019On the Inductive Bias of Neural Tangent Kernelscited by 177
  3. 2021BACON: Band-limited Coordinate Networks for Multiscale Scene Representationcited by 143
  4. 2019The Convergence Rate of Neural Networks for Learned Functions of Different Frequenciescited by 135
  5. 2021Neural Lumigraph Renderingcited by 105
  6. 2021A Structured Dictionary Perspective on Implicit Neural Representationscited by 100
  7. 2022E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Contextcited by 76
  8. 2022ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfercited by 75
  9. 2021ACORN: Adaptive Coordinate Networks for Neural Scene Representationcited by 65
  10. 2021Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fieldscited by 48
  11. 2020Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximationcited by 39
  12. 2022Scalable Neural Video Representations with Learnable Positional Featurescited by 29
  13. 2021ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representationcited by 16
  14. 2022Neural Residual Flow Fields for Efficient Video Representationscited by 16
  15. 2020Learning Unknown Physics of non-Newtonian Fluidscited by 13

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 14; 2025: 9; 2026: 2.

30 papers.

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  1. 2023FINER: Flexible spectral-bias tuning in Implicit NEural Representation by Variable-periodic Activation Functionscited by 78
  2. 2024Improved Implicit Neural Representation with Fourier Reparameterized Trainingcited by 36
  3. 2023Disorder-invariant Implicit Neural Representationcited by 27
  4. 2024Learning Transferable Features for Implicit Neural Representationscited by 14
  5. 2024FINER++: Building a Family of Variable-periodic Functions for Activating Implicit Neural Representationcited by 11
  6. 2023NeAI: A Pre-convoluted Representation for Plug-and-Play Neural Ambient Illuminationcited by 10
  7. 2023RHINO: Regularizing the Hash-based Implicit Neural Representationcited by 9
  8. 2024Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representationscited by 8
  9. 2024EVOS: Efficient Implicit Neural Training via EVOlutionary Selectorcited by 7
  10. 2024Implicit Neural Representations with Fourier Kolmogorov-Arnold Networkscited by 5
  11. 2024H-SIREN: Improving implicit neural representations with hyperbolic periodic functionscited by 5
  12. 2025Towards Lossless Implicit Neural Representation via Bit Plane Decompositioncited by 5
18 more
  1. 2024Enhancing Implicit Neural Representations via Symmetric Power Transformationcited by 4
  2. 2024Conv-INR: Convolutional Implicit Neural Representation for Multimodal Visual Signalscited by 2
  3. 2024Iterative approach to reconstructing neural disparity fields from light-field datacited by 2
  4. 2024Towards the Spectral bias Alleviation by Normalizations in Coordinate Networkscited by 2
  5. 2025MetricGrids: Arbitrary Nonlinear Approximation with Elementary Metric Grids based Implicit Neural Representationcited by 2
  6. 2025Exploring Kernel Transformations for Implicit Neural Representationscited by 2
  7. 2025Tree-NeRV: A Tree-Structured Neural Representation for Efficient Non-Uniform Video Encodingcited by 2
  8. 2025I-INR: Iterative Implicit Neural Representationscited by 2
  9. 2025NTK-Guided Implicit Neural Teachingcited by 2
  10. 2024Extreme Compression of Adaptive Neural Imagescited by 1
  11. 2024SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolutioncited by 1
  12. 2025QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representationscited by 1
  13. 2025MINR: Efficient Implicit Neural Representations for Multi-Image Encodingcited by 1
  14. 2025Distribution-Aware Hadamard Quantization for Hardware-Efficient Implicit Neural Representationscited by 1
  15. 2023Coordinate-based Neural Network for Fourier Phase Retrievalcited by 0
  16. 2024Streaming Neural Imagescited by 0
  17. 2026Fast Amortized Fitting of Scientific Signals Across Time and Ensembles via Transferable Neural Fieldscited by 0
  18. 2026PatchINR: Patch-Based Implicit Neural Representations for Efficient and Scalable Inferencecited by 0