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DNN-VolVis: Interactive Volume Visualization Supported by Deep Neural Network

https://doi.org/10.1109/pacificvis.2019.00041

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot

U-Net: Convolutional Networks for Biomedical Image Segmentation

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_47openalex-snapshot

Attribute2Image: Conditional Image Generation from Visual Attributes

inferredcites →https://doi.org/10.1007/978-3-658-40442-0_9openalex-snapshot

Generative Adversarial Nets

inferredcites →https://doi.org/10.1016/0893-6080(91)90009-topenalex-snapshot

Approximation capabilities of multilayer feedforward networks

inferredcites →https://doi.org/10.1038/323533a0openalex-snapshot

Learning representations by back-propagating errors

inferredcites →https://doi.org/10.1109/38.920623openalex-snapshot

The transfer function bake-off

inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot

Gradient-based learning applied to document recognition

inferredcites →https://doi.org/10.1109/83.535842openalex-snapshot

An image multiresolution representation for lossless and lossy compression

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.19openalex-snapshot

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

inferredcites →https://doi.org/10.1109/cvpr.2017.632openalex-snapshot

Image-to-Image Translation with Conditional Adversarial Networks

inferredcites →https://doi.org/10.1109/iccv.2017.244openalex-snapshot

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

inferredcites →https://doi.org/10.1109/iccv.2017.629openalex-snapshot

StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks

inferredcites →https://doi.org/10.1109/pacificvis.2013.6596129openalex-snapshot

Local WYSIWYG volume visualization

inferredcites →https://doi.org/10.1109/pccga.2002.1167880openalex-snapshot

ISpace: interactive volume data classification techniques using independent component analysis

inferredcites →https://doi.org/10.1109/svv.1998.729588openalex-snapshot

Semi-automatic generation of transfer functions for direct volume rendering

inferredcites →https://doi.org/10.1109/tvcg.2002.1021579openalex-snapshot

Multidimensional transfer functions for interactive volume rendering

inferredcites →https://doi.org/10.1109/tvcg.2005.38openalex-snapshot

An Intelligent System Approach to Higher-Dimensional Classification of Volume Data

inferredcites →https://doi.org/10.1109/tvcg.2006.148openalex-snapshot

High-Level User Interfaces for Transfer Function Design with Semantics

inferredcites →https://doi.org/10.1109/tvcg.2007.1051openalex-snapshot

Interactive Transfer Function Design Based on Editing Direct Volume Rendered Images

inferredcites →https://doi.org/10.1109/tvcg.2008.162openalex-snapshot

Size-based Transfer Functions: A New Volume Exploration Technique

inferredcites →https://doi.org/10.1109/tvcg.2009.189openalex-snapshot

The Occlusion Spectrum for Volume Classification and Visualization

inferredcites →https://doi.org/10.1109/tvcg.2009.25openalex-snapshot

Distribution-Driven Visualization of Volume Data

inferredcites →https://doi.org/10.1109/tvcg.2010.35openalex-snapshot

Visibility Histograms and Visibility-Driven Transfer Functions

inferredcites →https://doi.org/10.1109/tvcg.2011.261openalex-snapshot

WYSIWYG (What You See is What You Get) Volume Visualization

inferredcites →https://doi.org/10.1109/tvcg.2012.80openalex-snapshot

Scalable Multivariate Volume Visualization and Analysis Based on Dimension Projection and Parallel Coordinates

inferredcites →https://doi.org/10.1109/tvcg.2017.2744078openalex-snapshot

An Intelligent System Approach for Probabilistic Volume Rendering Using Hierarchical 3D Convolutional Sparse Coding

inferredcites →https://doi.org/10.1109/tvcg.2018.2816059openalex-snapshot

A Generative Model for Volume Rendering

inferredcites →https://doi.org/10.1109/vis.2005.31openalex-snapshot

Example-based Volume Illustrations

inferredcites →https://doi.org/10.1109/visual.1996.568113openalex-snapshot

Generation of transfer functions with stochastic search techniques

inferredcites →https://doi.org/10.1109/visual.1999.809932openalex-snapshot

Automating transfer function design for comprehensible volume rendering based on 3D field topology analysis

inferredcites →https://doi.org/10.1109/visual.2003.1250413openalex-snapshot

A novel interface for higher-dimensional classification of volume data

inferredcites →https://doi.org/10.1145/258734.258887openalex-snapshot

Design galleries

inferredcites →https://doi.org/10.1145/288126.288167openalex-snapshot

Semi-automatic generation of transfer functions for direct volume rendering

inferredcites →https://doi.org/10.1145/3065386openalex-snapshot

ImageNet classification with deep convolutional neural networks

inferredcites →https://doi.org/10.2312/vissym/eurovis05/271-278openalex-snapshot

Spatialized Transfer Functions

inferredcites →https://doi.org/10.2312/vissym/eurovis07/115-122openalex-snapshot

A Tri-Space Visualization Interface for Analyzing Time-Varying Multivariate Volume Data

inferredcites →https://doi.org/10.3156/jsoft.29.5_177_2openalex-snapshot

GAN（Generative Adversarial Nets）

inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot

AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)

inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot

Very Deep Convolutional Networks for Large-Scale Image Recognition

inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-snapshot

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

inferredcites →https://doi.org/10.48550/arxiv.1605.05396openalex-snapshot

Generative Adversarial Text to Image Synthesis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4813476openalex-extracted

An Unsupervised Method Based on Clustering and Two-Level Dimensionality Reduction for Transfer Function Definition and Design in Direct Volume Rendering

inferred← citeshttps://doi.org/10.1007/978-3-030-64556-4_16openalex-snapshot

Referenced Based Color Transfer for Medical Volume Rendering

inferred← citeshttps://doi.org/10.1007/978-3-031-62523-7_40openalex-snapshot

Visual Identification of Volumetric Structures from 3D Medical CT Data Using Density and Visibility-Based Quality Criteria

inferred← citeshttps://doi.org/10.1007/s00371-024-03368-5openalex-snapshot

Twinenet: coupling features for synthesizing volume rendered images via convolutional encoder–decoders and multilayer perceptrons

inferred← citeshttps://doi.org/10.1007/s00371-024-03596-9openalex-snapshot

Attention-driven visual emphasis for medical volumetric image visualization

inferred← citeshttps://doi.org/10.1007/s11554-021-01176-xopenalex-snapshot

A real-time image-centric transfer function design based on incremental classification

inferred← citeshttps://doi.org/10.1016/j.cag.2022.02.001openalex-snapshot

TSR-VFD: Generating temporal super-resolution for unsteady vector field data

inferred← citeshttps://doi.org/10.1016/j.visinf.2021.08.001openalex-snapshot

A survey of volume visualization techniques for feature enhancement

inferred← citeshttps://doi.org/10.1016/j.visinf.2022.04.004openalex-snapshot

VCNet: A generative model for volume completion

inferred← citeshttps://doi.org/10.1016/j.visinf.2024.04.003openalex-snapshot

Generative AI for visualization: State of the art and future directions

inferred← citeshttps://doi.org/10.1109/access.2021.3100429openalex-snapshot

Image-Based TF Colorization With CNN for Direct Volume Rendering

inferred← citeshttps://doi.org/10.1109/pacificvis48177.2020.8737openalex-snapshot

SSR-VFD: Spatial Super-Resolution for Vector Field Data Analysis and Visualization

inferred← citeshttps://doi.org/10.1109/pacificvis53943.2022.00012openalex-snapshot

Scalar2Vec: Translating Scalar Fields to Vector Fields via Deep Learning

inferred← citeshttps://doi.org/10.1109/pacificvis64226.2025.00029openalex-snapshot

ViSNeRF: Efficient Multidimensional Neural Radiance Field Representation for Visualization Synthesis of Dynamic Volumetric Scenes

inferred← citeshttps://doi.org/10.1109/pacificvis68791.2026.00029openalex-snapshot

REV-INR: Regularized Evidential Implicit Neural Representation for Uncertainty-Aware Volume Visualization

inferred← citeshttps://doi.org/10.1109/scw63240.2024.00045openalex-snapshot

Filling the Void: Data-Driven Machine Learning-based Reconstruction of Sampled Spatiotemporal Scientific Simulation Data

inferred← citeshttps://doi.org/10.1109/tim.2021.3111987openalex-snapshot

Multi-Material Interface Extraction and its Topological Relationship Expression for 3-D Image Data

inferred← citeshttps://doi.org/10.1109/tvcg.2020.3030344openalex-snapshot

Deep Volumetric Ambient Occlusion

inferred← citeshttps://doi.org/10.1109/tvcg.2020.3030346openalex-snapshot

V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data

inferred← citeshttps://doi.org/10.1109/tvcg.2020.3032123openalex-snapshot

SSR-TVD: Spatial Super-Resolution for Time-Varying Data Analysis and Visualization

inferred← citeshttps://doi.org/10.1109/tvcg.2021.3101418openalex-snapshot

S4: Self-Supervised Learning of Spatiotemporal Similarity

inferred← citeshttps://doi.org/10.1109/tvcg.2021.3106142openalex-snapshot

A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization

inferred← citeshttps://doi.org/10.1109/tvcg.2021.3114815openalex-snapshot

STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes

inferred← citeshttps://doi.org/10.1109/tvcg.2021.3127918openalex-snapshot

Volume Exploration Using Multidimensional Bhattacharyya Flow

inferred← citeshttps://doi.org/10.1109/tvcg.2022.3167896openalex-snapshot

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

inferred← citeshttps://doi.org/10.1109/tvcg.2022.3186146openalex-snapshot

Finding Nano-Ötzi: Cryo-Electron Tomography Visualization Guided by Learned Segmentation

inferred← citeshttps://doi.org/10.1109/tvcg.2023.3327371openalex-snapshot

Differentiable Design Galleries: A Differentiable Approach to Explore the Design Space of Transfer Functions

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3401755openalex-snapshot

Leveraging Self-Supervised Vision Transformers for Segmentation-Based Transfer Function Design

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3406959openalex-snapshot

Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3456338openalex-snapshot

ParamsDrag: Interactive Parameter Space Exploration via Image-Space Dragging

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3456342openalex-snapshot

StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualization

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3456360openalex-snapshot

Uncertainty-Aware Deep Neural Representations for Visual Analysis of Vector Field Data

inferred← citeshttps://doi.org/10.1109/tvcg.2024.3484471openalex-snapshot

Two-Level Transfer Functions Using t-SNE for Data Segmentation in Direct Volume Rendering

inferred← citeshttps://doi.org/10.1109/tvcg.2025.3567121openalex-snapshot

iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting

inferred← citeshttps://doi.org/10.1109/tvcg.2025.3633888openalex-snapshot

NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting

inferred← citeshttps://doi.org/10.1109/tvcg.2025.3642516openalex-snapshot

VolSegGS: Segmentation and Tracking in Dynamic Volumetric Scenes via Deformable 3D Gaussians

inferred← citeshttps://doi.org/10.1109/uncertaintyvisualization63963.2024.00013openalex-snapshot

Uncertainty-Informed Volume Visualization using Implicit Neural Representation

inferred← citeshttps://doi.org/10.1109/vis54862.2022.00040openalex-snapshot

Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles

inferred← citeshttps://doi.org/10.1111/cgf.14037openalex-snapshot

State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties

inferred← citeshttps://doi.org/10.1111/cgf.14526openalex-snapshot

SurfNet: Learning Surface Representations via Graph Convolutional Network

inferred← citeshttps://doi.org/10.1111/cgf.14955openalex-snapshot

Efficient Neural Representation of Volumetric Data using Coordinate‐Based Networks.

inferred← citeshttps://doi.org/10.1177/03019233241278460openalex-snapshot

Prospective on applying machine learning in computational fluid dynamics (CFD) simulation of metallurgical reactors

inferred← citeshttps://doi.org/10.11834/jig.230034openalex-snapshot

Intelligent visualization and visual analytics

inferred← citeshttps://doi.org/10.1186/s42774-022-00113-1openalex-snapshot

Deep learning approaches in flow visualization

inferred← citeshttps://doi.org/10.1615/jflowvisimageproc.2022041197openalex-snapshot

EXPLORATORY LAGRANGIAN-BASED PARTICLE TRACING USING DEEP LEARNING

inferred← citeshttps://doi.org/10.31219/osf.io/aw7rfopenalex-snapshot

Filling the Void: Deep Learning-based Reconstruction of Sampled Spatiotemporal Scientific Simulation Data

inferred← citeshttps://doi.org/10.4018/979-8-3693-3703-5.ch003openalex-snapshot

Generative AI for Visualization

inferred← citeshttps://doi.org/10.48550/arxiv.2106.05429openalex-snapshot

Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images

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