mlsanityData to 7 Oct 2026

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization

arXiv 2204.06504 ↗First posted 13 Apr 2022cs.GR cs.AI cs.CVcited by 32

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Abstract (arXiv)

Since 2016, we have witnessed the tremendous growth of artificial intelligence+visualization (AI+VIS) research. However, existing survey papers on AI+VIS focus on visual analytics and information visualization, not scientific visualization (SciVis). In this paper, we survey related deep learning (DL) works in SciVis, specifically in the direction of DL4SciVis: designing DL solutions for solving SciVis problems. To stay focused, we primarily consider works that handle scalar and vector field data but exclude mesh data. We classify and discuss these works along six dimensions: domain setting, research task, learning type, network architecture, loss function, and evaluation metric. The paper concludes with a discussion of the remaining gaps to fill along the discussed dimensions and the grand challenges we need to tackle as a community. This state-of-the-art survey guides SciVis researchers in gaining an overview of this emerging topic and points out future directions to grow this research.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Builds on 100 of its 189 references that are in the map. First posted on arXiv 13 Apr 2022.

Builds on

100 of 189 references.

References · 100

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Citing papers per year: 2022: 2; 2023: 6; 2024: 10; 2025: 7; 2026: 7.

32 papers.

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  1. 2023ChartReader: A Unified Framework for Chart Derendering and Comprehension without Heuristic Rulescited by 24
  2. 2024Generative AI for Visualization: State of the Art and Future Directionscited by 23
  3. 2023HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillationcited by 19
  4. 2025NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splattingcited by 19
  5. 2025iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splattingcited by 17
  6. 2023Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualizationcited by 16
  7. 2023ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasetscited by 16
  8. 2025Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representationcited by 11
  9. 2024StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualizationcited by 9
  10. 2025TexGS-VolVis: Expressive Scene Editing for Volume Visualization via Textured Gaussian Splattingcited by 9
  11. 2026SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agentscited by 9
  12. 2024ParamsDrag: Interactive Parameter Space Exploration via Image-Space Draggingcited by 6
20 more
  1. 2024FCNR: Fast Compressive Neural Representation of Visualization Imagescited by 6
  2. 2023FFEINR: Flow Feature-Enhanced Implicit Neural Representation for Spatio-temporal Super-Resolutioncited by 5
  3. 2022Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensemblescited by 3
  4. 2024Uncertainty-Aware Deep Neural Representations for Visual Analysis of Vector Field Datacited by 3
  5. 2024Uncertainty-Informed Volume Visualization using Implicit Neural Representationcited by 3
  6. 2025CD-TVD: Contrastive Diffusion for 3D Super-Resolution with Scarce High-Resolution Time-Varying Datacited by 3
  7. 2023Photon Field Networks for Dynamic Real-Time Volumetric Global Illuminationcited by 2
  8. 2024Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesiscited by 2
  9. 2024Adversarial Attacks on Machine Learning-Aided Visualizationscited by 2
  10. 2026Efficient Compression of Structured and Unstructured Volumes via Learned 3D Gaussian Representationcited by 2
  11. 2026ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualizationcited by 2
  12. 2022Monocular Depth Decomposition of Semi-Transparent Volume Renderingscited by 1
  13. 2025Topology Guidance: Controlling the Outputs of Generative Models via Vector Field Topologycited by 1
  14. 2026HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualizationcited by 1
  15. 2026Fixed-Budget Gaussian Volume Encoding with Structure-Aware Allocationcited by 1
  16. 2024VortexViz: Finding Vortex Boundaries by Learning from Particle Trajectoriescited by 0
  17. 2024A Comparative Study of Neural Surface Reconstruction for Scientific Visualizationcited by 0
  18. 2025Compressive Modeling and Visualization of Multivariate Scientific Data using Implicit Neural Representationcited by 0
  19. 2026Lossless-INR: Lossless Volumetric Implicit Neural Representationscited by 0
  20. 2026EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Databasecited by 0