research-article

Open access

Rip-NeRF: Anti-aliasing Radiance Fields with Ripmap-Encoded Platonic Solids

Authors:

Hao ZhaoAuthors Info & Claims

SIGGRAPH '24: ACM SIGGRAPH 2024 Conference Papers

Article No.: 125, Pages 1 - 11

https://doi.org/10.1145/3641519.3657402

Published: 13 July 2024 Publication History

All formats PDF

Abstract

Despite significant advancements in Neural Radiance Fields (NeRFs), the renderings may still suffer from aliasing and blurring artifacts, since it remains a fundamental challenge to effectively and efficiently characterize anisotropic areas induced by the cone-casting procedure. This paper introduces a Ripmap-Encoded Platonic Solid representation to precisely and efficiently featurize 3D anisotropic areas, achieving high-fidelity anti-aliased renderings. Central to our approach are two key components: Platonic Solid Projection and Ripmap encoding. The Platonic Solid Projection factorizes the 3D space onto the unparalleled faces of a certain Platonic solid, such that the anisotropic 3D areas can be projected onto planes with distinguishable characterization. Meanwhile, each face of the Platonic solid is encoded by the Ripmap encoding, which is constructed by anisotropically pre-filtering a learnable feature grid, to enable featurzing the projected anisotropic areas both precisely and efficiently by the anisotropic area-sampling. Extensive experiments on both well-established synthetic datasets and a newly captured real-world dataset demonstrate that our Rip-NeRF attains state-of-the-art rendering quality, particularly excelling in the fine details of repetitive structures and textures, while maintaining relatively swift training times, as shown in Fig. 1. The source code and data for this paper are at https://github.com/JunchenLiu77/Rip-NeRF.

Supplemental Material

MP4 File - presentation

presentation

Download
427.65 MB

References

[1]

Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan. 2021. Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields. In ICCV.

[2]

Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman. 2022. Mip-nerf 360: Unbounded anti-aliased neural radiance fields. In CVPR.

[3]

Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman. 2023. Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields. In ICCV.

[4]

Yash Belhe, Michaël Gharbi, Matthew Fisher, Iliyan Georgiev, Ravi Ramamoorthi, and Tzu-Mao Li. 2023. Discontinuity-Aware 2D Neural Fields. ACM Transactions on Graphics (TOG) 42, 6 (2023), 1–11.

Digital Library

[5]

Mojtaba Bemana, Karol Myszkowski, Jeppe Revall Frisvad, Hans-Peter Seidel, and Tobias Ritschel. 2022. Eikonal fields for refractive novel-view synthesis. In ACM SIGGRAPH 2022 Conference Proceedings. 1–9.

Digital Library

[6]

Ang Cao and Justin Johnson. 2023. Hexplane: A fast representation for dynamic scenes. In CVPR.

[7]

Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J Guibas, Jonathan Tremblay, Sameh Khamis, 2022. Efficient geometry-aware 3D generative adversarial networks. In CVPR.

[8]

Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su. 2022. Tensorf: Tensorial radiance fields. In ECCV.

[9]

Anpei Chen, Zexiang Xu, Xinyue Wei, Siyu Tang, Hao Su, and Andreas Geiger. 2023b. Dictionary fields: Learning a neural basis decomposition. ACM Transactions on Graphics (TOG) 42, 4 (2023), 1–12.

Digital Library

[10]

Xiaoxue Chen, Junchen Liu, Hao Zhao, Guyue Zhou, and Ya-Qin Zhang. 2023a. Nerrf: 3d reconstruction and view synthesis for transparent and specular objects with neural refractive-reflective fields. arXiv preprint arXiv:2309.13039 (2023).

[11]

Zheng Dong, Ke Xu, Yaoan Gao, Qilin Sun, Hujun Bao, Weiwei Xu, and Rynson WH Lau. 2023. SAILOR: Synergizing Radiance and Occupancy Fields for Live Human Performance Capture. ACM Transactions on Graphics (TOG) 42, 6 (2023), 1–15.

Digital Library

[12]

Hao-Bin Duan, Miao Wang, Jin-Chuan Shi, Xu-Chuan Chen, and Yan-Pei Cao. 2023. BakedAvatar: Baking Neural Fields for Real-Time Head Avatar Synthesis. ACM Transactions on Graphics (TOG) 42, 6 (2023), 1–17.

Digital Library

[13]

Daniel Duckworth, Peter Hedman, Christian Reiser, Peter Zhizhin, Jean-François Thibert, Mario Lučić, Richard Szeliski, and Jonathan T Barron. 2023. SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration. arXiv preprint arXiv:2312.07541 (2023).

[14]

Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, and Angjoo Kanazawa. 2023. K-planes: Explicit radiance fields in space, time, and appearance. In CVPR.

[15]

Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa. 2022. Plenoxels: Radiance fields without neural networks. In CVPR.

[16]

Bingchen Gong, Yuehao Wang, Xiaoguang Han, and Qi Dou. 2023. SeamlessNeRF: Stitching Part NeRFs with Gradient Propagation. In SIGGRAPH Asia 2023 Conference Papers. 1–10.

[17]

Kunal Gupta, Milos Hasan, Zexiang Xu, Fujun Luan, Kalyan Sunkavalli, Xin Sun, Manmohan Chandraker, and Sai Bi. 2023. MCNeRF: Monte Carlo Rendering and Denoising for Real-Time NeRFs. In SIGGRAPH Asia 2023 Conference Papers. 1–11.

[18]

Paul S. Heckbert. 1986. Survey of Texture Mapping. IEEE Computer Graphics and Applications 6, 11 (1986), 56–67. https://doi.org/10.1109/MCG.1986.276672

Digital Library

[19]

Wenbo Hu, Yuling Wang, Lin Ma, Bangbang Yang, Lin Gao, Xiao Liu, and Yuewen Ma. 2023. Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields. In ICCV.

[20]

Yi-Hua Huang, Yan-Pei Cao, Yu-Kun Lai, Ying Shan, and Lin Gao. 2023. NeRF-texture: Texture synthesis with neural radiance fields. In ACM SIGGRAPH 2023 Conference Proceedings. 1–10.

Digital Library

[21]

Mustafa Işık, Martin Rünz, Markos Georgopoulos, Taras Khakhulin, Jonathan Starck, Lourdes Agapito, and Matthias Nießner. 2023. Humanrf: High-fidelity neural radiance fields for humans in motion. arXiv preprint arXiv:2305.06356 (2023).

[22]

Kaiwen Jiang, Shu-Yu Chen, Hongbo Fu, and Lin Gao. 2023. NeRFFaceLighting: Implicit and Disentangled Face Lighting Representation Leveraging Generative Prior in Neural Radiance Fields. ACM Transactions on Graphics 42, 3 (2023), 1–18.

Digital Library

[23]

Kaiwen Jiang, Shu-Yu Chen, Feng-Lin Liu, Hongbo Fu, and Lin Gao. 2022. NeRFFaceEditing: Disentangled face editing in neural radiance fields. In SIGGRAPH Asia 2022 Conference Papers. 1–9.

Digital Library

[24]

Animesh Karnewar, Tobias Ritschel, Oliver Wang, and Niloy Mitra. 2022. Relu fields: The little non-linearity that could. In ACM SIGGRAPH 2022 Conference Proceedings.

Digital Library

[25]

Benjamin Keinert, Matthias Innmann, Michael Sänger, and Marc Stamminger. 2015. Spherical fibonacci mapping. ACM Transactions on Graphics (TOG) 34, 6 (2015), 1–7.

Digital Library

[26]

Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis. 2023. 3D Gaussian Splatting for Real-Time Radiance Field Rendering. ACM Transactions on Graphics 42, 4 (July 2023). https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/

Digital Library

[27]

Tobias Kirschstein, Shenhan Qian, Simon Giebenhain, Tim Walter, and Matthias Nießner. 2023. NeRSemble: Multi-view Radiance Field Reconstruction of Human Heads. arXiv preprint arXiv:2305.03027 (2023).

[28]

Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, and Timo Aila. 2020. Modular Primitives for High-Performance Differentiable Rendering. TOG 39, 6 (2020).

[29]

Yixing Lao, Xiaogang Xu, Xihui Liu, Hengshuang Zhao, 2024. CorresNeRF: Image Correspondence Priors for Neural Radiance Fields. Advances in Neural Information Processing Systems 36 (2024).

[30]

Ruilong Li, Matthew Tancik, and Angjoo Kanazawa. 2022. NerfAcc: A General NeRF Accleration Toolbox.arXiv preprint arXiv:2210.04847 (2022).

[31]

Zilu Li, Guandao Yang, Xi Deng, Christopher De Sa, Bharath Hariharan, and Steve Marschner. 2023. Neural Caches for Monte Carlo Partial Differential Equation Solvers. In SIGGRAPH Asia 2023 Conference Papers. 1–10.

[32]

Gao Lin, Liu Feng-Lin, Chen Shu-Yu, Jiang Kaiwen, Li Chunpeng, Yukun Lai, and Fu Hongbo. 2023. SketchFaceNeRF: Sketch-based facial generation and editing in neural radiance fields. ACM Transactions on Graphics (2023).

[33]

Haotong Lin, Sida Peng, Zhen Xu, Yunzhi Yan, Qing Shuai, Hujun Bao, and Xiaowei Zhou. 2022. Efficient neural radiance fields for interactive free-viewpoint video. In SIGGRAPH Asia 2022 Conference Papers. 1–9.

Digital Library

[34]

Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh. 2019. Neural Volumes: Learning Dynamic Renderable Volumes from Images. TOG 38, 4 (2019), 65:1–65:14.

Digital Library

[35]

Ilya Loshchilov and Frank Hutter. 2019. Decoupled weight decay regularization. In ICLR.

[36]

Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth. 2021. Nerf in the wild: Neural radiance fields for unconstrained photo collections. In CVPR.

[37]

Tom McReynolds, David Blythe, Brad Grantham, and Scott Nelson. 1998. Advanced graphics programming techniques using OpenGL. Computer Graphics (1998), 95–145.

[38]

Ben Mildenhall, Pratul P Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar. 2019. Local light field fusion: Practical view synthesis with prescriptive sampling guidelines. TOG 38, 4 (2019), 1–14.

Digital Library

[39]

Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. 2020. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. In ECCV.

[40]

Thomas Müller. 2021. tiny-cuda-nn. https://github.com/NVlabs/tiny-cuda-nn

[41]

Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller. 2022. Instant neural graphics primitives with a multiresolution hash encoding. TOG 41, 4 (2022), 1–15.

Digital Library

[42]

Keunhong Park, Philipp Henzler, Ben Mildenhall, Jonathan T Barron, and Ricardo Martin-Brualla. 2023a. CamP: Camera Preconditioning for Neural Radiance Fields. SIGGRAPH Asia (2023).

[43]

Keunhong Park, Philipp Henzler, Ben Mildenhall, Jonathan T Barron, and Ricardo Martin-Brualla. 2023b. CamP: Camera preconditioning for neural radiance fields. ACM Transactions on Graphics (TOG) 42, 6 (2023), 1–11.

Digital Library

[44]

Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, and Steven M Seitz. 2021. Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields. arXiv preprint arXiv:2106.13228 (2021).

[45]

Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, 2019. PyTorch: An imperative style, high-performance deep learning library. In NeurIPS.

[46]

Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger. 2020. Convolutional occupancy networks. In ECCV.

[47]

Ziqiao Peng, Wentao Hu, Yue Shi, Xiangyu Zhu, Xiaomei Zhang, Hao Zhao, Jun He, Hongyan Liu, and Zhaoxin Fan. 2023. SyncTalk: The Devil is in the Synchronization for Talking Head Synthesis. arXiv preprint arXiv:2311.17590 (2023).

[48]

Christian Reiser, Rick Szeliski, Dor Verbin, Pratul Srinivasan, Ben Mildenhall, Andreas Geiger, Jon Barron, and Peter Hedman. 2023. Merf: Memory-efficient radiance fields for real-time view synthesis in unbounded scenes. ACM Transactions on Graphics (TOG) 42, 4 (2023), 1–12.

Digital Library

[49]

Zixi Shu, Ran Yi, Yuqi Meng, Yutong Wu, and Lizhuang Ma. 2023. RT-Octree: Accelerate PlenOctree Rendering with Batched Regular Tracking and Neural Denoising for Real-time Neural Radiance Fields. In SIGGRAPH Asia 2023 Conference Papers. 1–11.

[50]

Vincent Sitzmann, Michael Zollhoefer, and Gordon Wetzstein. 2019. Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations. NeurIPS.

[51]

Nagabhushan Somraj, Adithyan Karanayil, and Rajiv Soundararajan. 2023. SimpleNeRF: Regularizing Sparse Input Neural Radiance Fields with Simpler Solutions. In SIGGRAPH Asia 2023 Conference Papers. 1–11.

[52]

Nagabhushan Somraj and Rajiv Soundararajan. 2023. ViP-NeRF: Visibility Prior for Sparse Input Neural Radiance Fields. arXiv preprint arXiv:2305.00041 (2023).

[53]

Cheng Sun, Min Sun, and Hwann-Tzong Chen. 2022. Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In CVPR.

[54]

Towaki Takikawa, Alex Evans, Jonathan Tremblay, Thomas Müller, Morgan McGuire, Alec Jacobson, and Sanja Fidler. 2022. Variable bitrate neural fields. In ACM SIGGRAPH 2022 Conference Proceedings. 1–9.

Digital Library

[55]

Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, 2023. Nerfstudio: A modular framework for neural radiance field development. In ACM SIGGRAPH 2023 Conference Proceedings. 1–12.

Digital Library

[56]

Alex Trevithick, Matthew Chan, Michael Stengel, Eric Chan, Chao Liu, Zhiding Yu, Sameh Khamis, Manmohan Chandraker, Ravi Ramamoorthi, and Koki Nagano. 2023. Real-time radiance fields for single-image portrait view synthesis. ACM Transactions on Graphics (TOG) 42, 4 (2023), 1–15.

Digital Library

[57]

Daoye Wang, Prashanth Chandran, Gaspard Zoss, Derek Bradley, and Paulo Gotardo. 2022. Morf: Morphable radiance fields for multiview neural head modeling. In ACM SIGGRAPH 2022 Conference Proceedings. 1–9.

Digital Library

[58]

Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang. 2021. NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction. NeurIPS (2021).

[59]

Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004. Image quality assessment: from error visibility to structural similarity. TIP 13, 4 (2004), 600–612.

Digital Library

[60]

Yuxi Wei, Zi Wang, Yifan Lu, Chenxin Xu, Changxing Liu, Hao Zhao, Siheng Chen, and Yanfeng Wang. 2024. Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents. arXiv preprint arXiv:2402.05746 (2024).

[61]

Kin-Ming Wong and Tien-Tsin Wong. 2018. Spherical blue noise. In Proceedings of the 26th Pacific Conference on Computer Graphics and Applications: Short Papers. 5–8.

Digital Library

[62]

Jiangkai Wu, Liming Liu, Yunpeng Tan, Quanlu Jia, Haodan Zhang, and Xinggong Zhang. 2023b. ActRay: Online Active Ray Sampling for Radiance Fields. In SIGGRAPH Asia 2023 Conference Papers. 1–10.

[63]

Tong Wu, Jia-Mu Sun, Yu-Kun Lai, and Lin Gao. 2023c. De-nerf: Decoupled neural radiance fields for view-consistent appearance editing and high-frequency environmental relighting. In ACM SIGGRAPH 2023 conference proceedings. 1–11.

Digital Library

[64]

Xiuchao Wu, Jiamin Xu, Xin Zhang, Hujun Bao, Qixing Huang, Yujun Shen, James Tompkin, and Weiwei Xu. 2023d. ScaNeRF: Scalable Bundle-Adjusting Neural Radiance Fields for Large-Scale Scene Rendering. ACM Transactions on Graphics (TOG) 42, 6 (2023), 1–18.

Digital Library

[65]

Zirui Wu, Tianyu Liu, Liyi Luo, Zhide Zhong, Jianteng Chen, Hongmin Xiao, Chao Hou, Haozhe Lou, Yuantao Chen, Runyi Yang, 2023a. Mars: An instance-aware, modular and realistic simulator for autonomous driving. In CAAI International Conference on Artificial Intelligence. Springer, 3–15.

[66]

Yuelang Xu, Hongwen Zhang, Lizhen Wang, Xiaochen Zhao, Han Huang, Guojun Qi, and Yebin Liu. 2023. LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar. arXiv preprint arXiv:2305.01190 (2023).

[67]

Han Yan, Celong Liu, Chao Ma, and Xing Mei. 2023. PlenVDB: Memory Efficient VDB-Based Radiance Fields for Fast Training and Rendering. In CVPR.

[68]

Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, and Angjoo Kanazawa. 2021. Plenoctrees for real-time rendering of neural radiance fields. In ICCV.

[69]

Shiran Yuan and Hao Zhao. 2023. SlimmeRF: Slimmable Radiance Fields. arXiv preprint arXiv:2312.10034 (2023).

[70]

Chong Zeng, Guojun Chen, Yue Dong, Pieter Peers, Hongzhi Wu, and Xin Tong. 2023. Relighting Neural Radiance Fields with Shadow and Highlight Hints. In ACM SIGGRAPH 2023 Conference Proceedings. 1–11.

[71]

Jingbo Zhang, Xiaoyu Li, Ziyu Wan, Can Wang, and Jing Liao. 2022b. Fdnerf: Few-shot dynamic neural radiance fields for face reconstruction and expression editing. In SIGGRAPH Asia 2022 Conference Papers. 1–9.

Digital Library

[72]

Qiang Zhang, Seung-Hwan Baek, Szymon Rusinkiewicz, and Felix Heide. 2022a. Differentiable point-based radiance fields for efficient view synthesis. In SIGGRAPH Asia 2022 Conference Papers. 1–12.

Digital Library

[73]

Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang. 2018. The unreasonable effectiveness of deep features as a perceptual metric. In CVPR.

[74]

Zerong Zheng, Xiaochen Zhao, Hongwen Zhang, Boning Liu, and Yebin Liu. 2023. AvatarReX: Real-time Expressive Full-body Avatars. arXiv preprint arXiv:2305.04789 (2023).

[75]

Qiang Zhou, Weize Li, Lihan Jiang, Guoliang Wang, Guyue Zhou, Shanghang Zhang, and Hao Zhao. 2024. Pad: A dataset and benchmark for pose-agnostic anomaly detection. Advances in Neural Information Processing Systems 36 (2024).

[76]

Zhenxin Zhu, Yuantao Chen, Zirui Wu, Chao Hou, Yongliang Shi, Chuxuan Li, Pengfei Li, Hao Zhao, and Guyue Zhou. 2023. Latitude: Robotic global localization with truncated dynamic low-pass filter in city-scale nerf. In 2023 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 8326–8332.

[77]

Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R Oswald, and Marc Pollefeys. 2022. Nice-slam: Neural implicit scalable encoding for slam. In CVPR.

[78]

Jingyu Zhuang, Chen Wang, Liang Lin, Lingjie Liu, and Guanbin Li. 2023. Dreameditor: Text-driven 3d scene editing with neural fields. In SIGGRAPH Asia 2023 Conference Papers. 1–10.

Digital Library

Cited By

Liu HTan YBhojan A(2025)Efficient Multi-Bounce Ray Tracing for Specular and Transparent Materials in NeRF2025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)10.1109/AIxVR63409.2025.00068(362-368)Online publication date: 27-Jan-2025
https://doi.org/10.1109/AIxVR63409.2025.00068

Index Terms

Rip-NeRF: Anti-aliasing Radiance Fields with Ripmap-Encoded Platonic Solids
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Reconstruction
      2. Computer vision representations
        Hierarchical representations

Recommendations

2D Gaussian Splatting for Geometrically Accurate Radiance Fields
SIGGRAPH '24: ACM SIGGRAPH 2024 Conference Papers

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed. However, 3DGS fails to accurately represent surfaces due to the multi-view inconsistent nature ...
Aggregate G-buffer anti-aliasing
i3D '15: Proceedings of the 19th Symposium on Interactive 3D Graphics and Games

We present Aggregate G-Buffer Anti-Aliasing (AGAA), a new technique for efficient anti-aliased deferred rendering of complex geometry using modern graphics hardware. In geometrically complex situations, where many surfaces intersect a pixel, current ...
Decoupled coverage anti-aliasing
HPG '15: Proceedings of the 7th Conference on High-Performance Graphics

State-of-the-art methods for geometric anti-aliasing in real-time rendering are based on Multi-Sample Anti-Aliasing (MSAA), which samples visibility more than shading to reduce the number of expensive shading calculations. However, for high-quality ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGGRAPH '24: ACM SIGGRAPH 2024 Conference Papers

July 2024

1106 pages

ISBN:9798400705250

DOI:10.1145/3641519

Copyright © 2024 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2024

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

SIGGRAPH '24

Sponsor:

SIGGRAPH

SIGGRAPH '24: Special Interest Group on Computer Graphics and Interactive Techniques Conference

July 27 - August 1, 2024

CO, Denver, USA

Acceptance Rates

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
508
Total Downloads

Downloads (Last 12 months)508
Downloads (Last 6 weeks)66

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Liu HTan YBhojan A(2025)Efficient Multi-Bounce Ray Tracing for Specular and Transparent Materials in NeRF2025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)10.1109/AIxVR63409.2025.00068(362-368)Online publication date: 27-Jan-2025
https://doi.org/10.1109/AIxVR63409.2025.00068

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Figures

Tables

Media

View Table of Conten