mlsanityData to 14 Oct 2026

H-SIREN: Improving implicit neural representations with hyperbolic periodic functions

arXiv 2410.04716 ↗First posted 7 Oct 2024cs.CVcited by 5

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Abstract (arXiv)

Implicit neural representations (INR) have been recently adopted in various applications ranging from computer vision tasks to physics simulations by solving partial differential equations. Among existing INR-based works, multi-layer perceptrons with sinusoidal activation functions find widespread applications and are also frequently treated as a baseline for the development of better activation functions for INR applications. Recent investigations claim that the use of sinusoidal activation functions could be sub-optimal due to their limited supported frequency set as well as their tendency to generate over-smoothed solutions. We provide a simple solution to mitigate such an issue by changing the activation function at the first layer from sin(x) to sin(sinh(2x)). We demonstrate H-SIREN in various computer vision and fluid flow problems, where it surpasses the performance of several state-of-the-art INRs.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 34 of its 44 references that are in the map. First posted on arXiv 7 Oct 2024.

Builds on

34 of 44 references.

References · 34

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22 more
  1. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 861
  2. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  3. 2021Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapescited by 426
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  8. 2021A Structured Dictionary Perspective on Implicit Neural Representationscited by 100
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  10. 2023Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolutioncited by 33
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  12. 2022DINER: Disorder-Invariant Implicit Neural Representationcited by 30
  13. 2022Residual Multiplicative Filter Networks for Multiscale Reconstructioncited by 25
  14. 2024A Sampling Theory Perspective on Activations for Implicit Neural Representationscited by 24
  15. 2022A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulationscited by 14
  16. 2023FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenescited by 14
  17. 2022NeuralGrasps: Learning Implicit Representations for Grasps of Multiple Robotic Handscited by 12
  18. 2023Learning Spatially Collaged Fourier Bases for Implicit Neural Representationcited by 11
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025ARC: Anchored Representation Clouds for High-Resolution INR Classificationcited by 3
  2. 2025Enhancing Transformers Through Conditioned Embedded Tokenscited by 3
  3. 2025I-INR: Iterative Implicit Neural Representationscited by 2
  4. 2025Squeeze3D: Extreme Neural Compression with Latent Space Bridgingcited by 0
  5. 2026The Inlet Rank Collapse in Implicit Neural Representations: Diagnosis and Unified Remedycited by 0