The DOI matches its Crossref record.
Ray tracing volume densities
Abstract
This paper presents new algorithms to trace objects represented by densities within a volume grid, e.g. clouds, fog, flames, dust, particle systems. We develop the light scattering equations, discuss previous methods of solution, and present a new approximate solution to the full three-dimensional radiative scattering problem suitable for use in computer graphics. Additionally we review dynamical models for clouds used to make an animated movie.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., & Ng, R. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58452-8_24 · Cited by 5,351
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
Chan, E. R., Monteiro, M., Kellnhofer, P., Wu, J., & Wetzstein, G. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00574 · Cited by 689
Neural Articulated Radiance Field
Noguchi, A., Sun, X., Lin, S., & Harada, T. (2021) · arXiv · doi:10.48550/arxiv.2104.03110 · Cited by 177
NodeSLAM: Neural object descriptors for multi-view shape reconstruction
Sucar, E., Wada, K., & Davison, A. (2020) · 2020 International Conference on 3D Vision (3DV) · doi:10.1109/3dv50981.2020.00105 · Cited by 108
A Survey on Deep Generative 3D-aware Image Synthesis
Xia, W., & Xue, J.-H. (2024) · ACM Computing Surveys · doi:10.1145/3626193 · Cited by 20
Metadata
- Authors
- Kajiya, J. T., & Von Herzen, B. P.
- Venue
- ACM SIGGRAPH Computer Graphics
- Published
- 1984-01
- Volume
- 18
- Issue
- 3
- Pages
- 165-174
- ISSN
- 0097-8930 (ISSN-L)
- OpenAlex
- W4237648096
- Cited by
- 706
- References
- 0
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Ray tracing volume densities. https://app.cochat.ai/papers/10.1145/964965.808594
- The paper
- Kajiya, J. T., & Von Herzen, B. P. (1984). Ray tracing volume densities. ACM SIGGRAPH Computer Graphics. https://doi.org/10.1145/964965.808594
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
