mlsanityData to 14 Oct 2026

Interactive Volume Visualization via Multi-Resolution Hash Encoding based Neural Representation

arXiv 2207.11620 ↗First posted 23 Jul 2022cs.GR cs.LGcited by 19

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Abstract (arXiv)

Neural networks have shown great potential in compressing volume data for visualization. However, due to the high cost of training and inference, such volumetric neural representations have thus far only been applied to offline data processing and non-interactive rendering. In this paper, we demonstrate that by simultaneously leveraging modern GPU tensor cores, a native CUDA neural network framework, and a well-designed rendering algorithm with macro-cell acceleration, we can interactively ray trace volumetric neural representations (10-60fps). Our neural representations are also high-fidelity (PSNR > 30dB) and compact (10-1000x smaller). Additionally, we show that it is possible to fit the entire training step inside a rendering loop and skip the pre-training process completely. To support extreme-scale volume data, we also develop an efficient out-of-core training strategy, which allows our volumetric neural representation training to potentially scale up to terascale using only an NVIDIA RTX 3090 workstation.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 18 of its 61 references that are in the map. First posted on arXiv 23 Jul 2022.

Builds on

18 of 61 references.

References · 18

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  4. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  5. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  6. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  7. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  8. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
  9. 2017Convolutional Sequence to Sequence Learningcited by 552
  10. 2021Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapescited by 426
  11. 2018Neural Importance Samplingcited by 155
  12. 2021Real-time Neural Radiance Caching for Path Tracingcited by 91
6 more
  1. 2021Compressive Neural Representations of Volumetric Scalar Fieldscited by 64
  2. 2018TTHRESH: Tensor Compression for Multidimensional Visual Datacited by 42
  3. 2021Neural Radiositycited by 33
  4. 2021Fast Neural Representations for Direct Volume Renderingcited by 32
  5. 2021Deep Hierarchical Super Resolution for Scientific Datacited by 12
  6. 2019Efficient Space Skipping and Adaptive Sampling of Unstructured Volumes Using Hardware Accelerated Ray Tracingcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 2; 2025: 4; 2026: 10.

19 papers.

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  1. 2025iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splattingcited by 18
  2. 2023ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasetscited by 17
  3. 2024StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualizationcited by 9
  4. 2023Distributed Neural Representation for Reactive in situ Visualizationcited by 8
  5. 2025Explorable INR: An Implicit Neural Representation for Ensemble Simulation Enabling Efficient Spatial and Parameter Explorationcited by 8
  6. 2024Regularized Multi-Decoder Ensemble for an Error-Aware Scene Representation Networkcited by 6
  7. 2025GSCache: Real-Time Radiance Caching for Volume Path Tracing using 3D Gaussian Splattingcited by 5
  8. 2026Neural Harmonic Textures for High-Quality Primitive Based Neural Reconstructioncited by 4
  9. 2025F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encodingcited by 3
  10. 2023Photon Field Networks for Dynamic Real-Time Volumetric Global Illuminationcited by 2
  11. 2026Efficient Compression of Structured and Unstructured Volumes via Learned 3D Gaussian Representationcited by 2
  12. 2026REV-INR: Regularized Evidential Implicit Neural Representation for Uncertainty-Aware Volume Visualizationcited by 1
7 more
  1. 2026Fixed-Budget Gaussian Volume Encoding with Structure-Aware Allocationcited by 1
  2. 2026NeuVolEx: Implicit Neural Features for Volume Explorationcited by 0
  3. 2026Fast Amortized Fitting of Scientific Signals Across Time and Ensembles via Transferable Neural Fieldscited by 0
  4. 2026Lossless-INR: Lossless Volumetric Implicit Neural Representationscited by 0
  5. 2026EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Databasecited by 0
  6. 20263D Field Data Reduction with Adaptive Sample-Based Gaussian-Encoded Reconstructioncited by 0
  7. 2026DiffusionShadow: Diffusion-based Shadow Caching for Neural Volume Renderingcited by 0