The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Instant neural graphics primitives with a multiresolution hash encoding
Open accessAbstract
Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that permits the use of a smaller network without sacrificing quality, thus significantly reducing the number of floating point and memory access operations: a small neural network is augmented by a multiresolution hash table of trainable feature vectors whose values are optimized through stochastic gradient descent. The multiresolution structure allows the network to disambiguate hash collisions, making for a simple architecture that is trivial to parallelize on modern GPUs. We leverage this parallelism by implementing the whole system using fully-fused CUDA kernels with a focus on minimizing wasted bandwidth and compute operations. We achieve a combined speedup of several orders of magnitude, enabling training of high-quality neural graphics primitives in a matter of seconds, and rendering in tens of milliseconds at a resolution of 1920×1080.
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Cites
Convolutional Sequence to Sequence Learning
Gehring, J., Auli, M., Grangier, D., Yarats, D., & Dauphin, Y. N. (2017) · arXiv · doi:10.48550/arxiv.1705.03122 · Cited by 2,850 · cited 1×
“For neural networks, input encodings have proven useful in the attention components of recurrent architectures [Gehring et al. 2017] and, subsequently, transformers [Vaswani et al.”
MethodMicikevicius, P., Narang, S., Alben, J., Diamos, G., Elsen, E., Garcia, D., Ginsburg, B., Houston, M., Kuchaiev, O., Venkatesh, G., et al. (2017) · arXiv · doi:10.48550/arxiv.1710.03740 · Cited by 1,179
Cited by
3D Gaussian Splatting for Real-Time Radiance Field Rendering
Kerbl, B., Kopanas, G., Leimkuehler, T., & Drettakis, G. (2023) · ACM Transactions on Graphics · doi:10.1145/3592433 · Cited by 6,025
“The directional appearance component (color) of the radiance field is represented via spherical harmonics (SH), following standard practice [Fridovich-Keil and Yu et al. 2022; Müller et al. 2022].”
BackgroundMethodResultInfluentialDeformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction
Yang, Z., Gao, X., Zhou, W., Jiao, S., Zhang, Y., & Jin, X. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52733.2024.01922 · Cited by 452
PixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction
Charatan, D., Li, S. L., Tagliasacchi, A., & Sitzmann, V. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52733.2024.01840 · Cited by 420
FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects
Wen, B., Yang, W., Kautz, J., & Birchfield, S. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52733.2024.01692 · Cited by 353
Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures
Metzer, G., Richardson, E., Patashnik, O., Giryes, R., & Cohen-Or, D. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.01218 · Cited by 336
Metadata
- Authors
- Müller, T., Evans, A., Schied, C., & Keller, A.
- Venue
- ACM Transactions on Graphics
- Published
- 2022-07
- Volume
- 41
- Issue
- 4
- Pages
- 1-15
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W4221151978
- Cited by
- 4,114
- References
- 2
- FWCI
- 1035.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
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