mlsanityData to 7 Oct 2026

FINER: Flexible spectral-bias tuning in Implicit NEural Representation by Variable-periodic Activation Functions

arXiv 2312.02434 ↗First posted 5 Dec 2023cs.CVcited by 77

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Abstract (arXiv)

Implicit Neural Representation (INR), which utilizes a neural network to map coordinate inputs to corresponding attributes, is causing a revolution in the field of signal processing. However, current INR techniques suffer from a restricted capability to tune their supported frequency set, resulting in imperfect performance when representing complex signals with multiple frequencies. We have identified that this frequency-related problem can be greatly alleviated by introducing variable-periodic activation functions, for which we propose FINER. By initializing the bias of the neural network within different ranges, sub-functions with various frequencies in the variable-periodic function are selected for activation. Consequently, the supported frequency set of FINER can be flexibly tuned, leading to improved performance in signal representation. We demonstrate the capabilities of FINER in the contexts of 2D image fitting, 3D signed distance field representation, and 5D neural radiance fields optimization, and we show that it outperforms existing INRs.

Key facts. Cited by 77 papers in the map (data through 7 Oct 2026). Builds on 28 of its 42 references that are in the map. First posted on arXiv 5 Dec 2023.

Builds on

28 of 42 references.

References · 28

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  2. 2018Neural Tangent Kernel: Convergence and Generalization in Neural Networkscited by 2,597
  3. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  4. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  6. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
  7. 2018On the Spectral Bias of Neural Networkscited by 1,321
  8. 2021Neural Fields in Visual Computing and Beyondcited by 539
  9. 2023Neuralangelo: High-Fidelity Neural Surface Reconstructioncited by 464
  10. 2021Advances in Neural Renderingcited by 365
  11. 2021NeRV: Neural Representations for Videoscited by 255
  12. 2021COIN: COmpression with Implicit Neural representationscited by 232
16 more
  1. 2023WIRE: Wavelet Implicit Neural Representationscited by 220
  2. 2021Implicit Neural Representations for Image Compressioncited by 161
  3. 2021BACON: Band-limited Coordinate Networks for Multiscale Scene Representationcited by 142
  4. 2021Layered Neural Atlases for Consistent Video Editingcited by 137
  5. 2021Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPscited by 134
  6. 2021HDR-NeRF: High Dynamic Range Neural Radiance Fieldscited by 113
  7. 2021A Structured Dictionary Perspective on Implicit Neural Representationscited by 100
  8. 2022Physics-Informed Machine Learning: A Survey on Problems, Methods and Applicationscited by 88
  9. 2022GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimationcited by 86
  10. 2022ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfercited by 73
  11. 2021Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fieldscited by 48
  12. 2022DINER: Disorder-Invariant Implicit Neural Representationcited by 30
  13. 2022Neural Fourier Filter Bankcited by 29
  14. 2023Polynomial Implicit Neural Representations For Large Diverse Datasetscited by 18
  15. 2023Inverting the Imaging Process by Learning an Implicit Camera Modelcited by 10
  16. 2023Neural Free-Viewpoint Relighting for Glossy Indirect Illuminationcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 15; 2025: 35; 2026: 27.

77 papers.

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  1. 2024Where Do We Stand with Implicit Neural Representations? A Technical and Performance Surveycited by 41
  2. 2024Tuning the Frequencies: Robust Training for Sinusoidal Neural Networkscited by 18
  3. 2024FreSh: Frequency Shifting for Accelerated Neural Representation Learningcited by 14
  4. 2024MiraGe: Editable 2D Images using Gaussian Splattingcited by 12
  5. 2024Fast Training of Sinusoidal Neural Fields via Scaling Initializationcited by 11
  6. 2024FINER++: Building a Family of Variable-periodic Functions for Activating Implicit Neural Representationcited by 10
  7. 2024Neural Experts: Mixture of Experts for Implicit Neural Representationscited by 9
  8. 2025F-INR: Functional Tensor Decomposition for Implicit Neural Representationscited by 6
  9. 2024H-SIREN: Improving implicit neural representations with hyperbolic periodic functionscited by 5
  10. 2024EVOS: Efficient Implicit Neural Training via EVOlutionary Selectorcited by 5
  11. 2025Towards Lossless Implicit Neural Representation via Bit Plane Decompositioncited by 5
  12. 2024Implicit Neural Representations with Fourier Kolmogorov-Arnold Networkscited by 4
38 more
  1. 2025A Unified Theory of Sinusoidal Activation Families for Implicit Neural Representationscited by 4
  2. 2025Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potentialcited by 4
  3. 2025Continuous Representation Methods, Theories, and Applications: An Overview and Perspectivescited by 4
  4. 2025Implicit Inversion turns CLIP into a Decodercited by 4
  5. 2024HOIN: High-Order Implicit Neural Representationscited by 3
  6. 2024Neural Video Representation for Redundancy Reduction and Consistency Preservationcited by 3
  7. 2025SASNet: Spatially-Adaptive Sinusoidal Networks for INRscited by 3
  8. 2024Towards the Spectral bias Alleviation by Normalizations in Coordinate Networkscited by 2
  9. 2025MetricGrids: Arbitrary Nonlinear Approximation with Elementary Metric Grids based Implicit Neural Representationcited by 2
  10. 2025LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encodingcited by 2
  11. 2025Exploring Kernel Transformations for Implicit Neural Representationscited by 2
  12. 2025V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopycited by 2
  13. 2025Cross-Frequency Implicit Neural Representation with Self-Evolving Parameterscited by 2
  14. 2025Tree-NeRV: A Tree-Structured Neural Representation for Efficient Non-Uniform Video Encodingcited by 2
  15. 2025SR-NeRV: Improving Embedding Efficiency of Neural Video Representation via Super-Resolutioncited by 2
  16. 2025VidFuncta: Towards Generalizable Neural Representations for Ultrasound Videoscited by 2
  17. 2025WIPES: Wavelet-based Visual Primitivescited by 2
  18. 2025Spectral Bottleneck in Sinusoidal Representation Networks: Noise is All You Needcited by 2
  19. 2025FM-SIREN & FM-FINER: Implicit Neural Representation Using Nyquist-based Orthogonalitycited by 2
  20. 2026Calibrated Harmonic Overlaid Implicit Neural Representations for Multi-Dimensional Datacited by 2
  21. 2024PNR: Physics-informed Neural Representation for high-resolution LFM reconstructioncited by 1
  22. 2025ARC-Flow : Articulated, Resolution-Agnostic, Correspondence-Free Matching and Interpolation of 3D Shapes Under Flow Fieldscited by 1
  23. 2025QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representationscited by 1
  24. 2025VI3NR: Variance Informed Initialization for Implicit Neural Representationscited by 1
  25. 2025COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representationscited by 1
  26. 2025MINR: Efficient Implicit Neural Representations for Multi-Image Encodingcited by 1
  27. 2025Distribution-Aware Hadamard Quantization for Hardware-Efficient Implicit Neural Representationscited by 1
  28. 2025High-Frequency First: A Two-Stage Approach for Improving Image INRcited by 1
  29. 2025On the accuracy of implicit neural representations for cardiovascular anatomies and hemodynamic fieldscited by 1
  30. 2025GaINeR: Geometry-Aware Implicit Network Representationcited by 1
  31. 2025A new initialisation to Control Gradients in Sinusoidal Neural networkcited by 1
  32. 2026Content-Aware Frequency Encoding for Implicit Neural Representations with Fourier-Chebyshev Featurescited by 1
  33. 2026Reparameterized Tensor Ring Functional Decomposition for Multi-Dimensional Data Recoverycited by 1
  34. 2026Implicit Neural Representations: A Signal Processing Perspectivecited by 1
  35. 2026Blockwise Stabilized Adaptive Cubic Regularization with Subsolvers via Recurrencecited by 1
  36. 2026Loss Landscape Features That Make Adam Stall: Definitions, Estimators, and the Preconditioned Hessian Viewcited by 1
  37. 2024SL2A-INR: Single-Layer Learnable Activation for Implicit Neural Representationcited by 0
  38. 2025Structure-Preserving Patch Decoding for Efficient Neural Video Representationcited by 0

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