liyang
ae28d55f81
Source: RGB-D -> Dyn-HaMR -> L20 retargeting -> FoundationPose -> reference repair -> SPIDER, documented in docs/PIPELINE_LATEST.md and docs/SETUP_AND_WEIGHTS.md. Adds FoundationPose and nvdiffrast upstream snapshots, requirements/pipeline_venv.txt and the FoundationPose weight manifest/downloader. Assets (Git LFS): weights/ (WiLoR detector, HandFlow denoiser, UniDepth-L), FoundationPose checkpoints, HaMeR checkpoint, Dyn-HaMR HMP model and BMC constraints, L20 URDF/meshes, the 20260915_171525 D405 recording and the two box CADs. MANO models are not redistributed (third_party/hamer/_DATA/data/mano/README.txt). Environments, caches and run outputs excluded. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
50 lines
2.2 KiB
Markdown
50 lines
2.2 KiB
Markdown
## Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering
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**Modular Primitives for High-Performance Differentiable Rendering**<br>
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Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila<br>
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[http://arxiv.org/abs/2011.03277](http://arxiv.org/abs/2011.03277)
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Nvdiffrast is a PyTorch library that provides high-performance primitive operations for rasterization-based differentiable rendering.
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To install:
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```
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pip install setuptools wheel ninja
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pip install git+https://github.com/NVlabs/nvdiffrast.git --no-build-isolation
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```
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See ☞☞ [nvdiffrast documentation](https://nvlabs.github.io/nvdiffrast) ☜☜ for more information.
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## Licenses
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Copyright © 2020–2025, NVIDIA Corporation. All rights reserved.
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This work is made available under the [Nvidia Source Code License](https://github.com/NVlabs/nvdiffrast/blob/main/LICENSE.txt).
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For business inquiries, please visit our website and submit the form: [NVIDIA Research Licensing](https://www.nvidia.com/en-us/research/inquiries/)
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We do not currently accept outside code contributions in the form of pull requests.
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Environment map stored as part of `samples/data/envphong.npz` is derived from a Wave Engine
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[sample material](https://github.com/WaveEngine/Samples-2.5/tree/master/Materials/EnvironmentMap/Content/Assets/CubeMap.cubemap)
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originally shared under
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[MIT License](https://github.com/WaveEngine/Samples-2.5/blob/master/LICENSE.md).
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Mesh and texture stored as part of `samples/data/earth.npz` are derived from
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[3D Earth Photorealistic 2K](https://www.turbosquid.com/3d-models/3d-realistic-earth-photorealistic-2k-1279125)
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model originally made available under
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[TurboSquid 3D Model License](https://blog.turbosquid.com/turbosquid-3d-model-license/#3d-model-license).
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## Citation
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```
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@article{Laine2020diffrast,
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title = {Modular Primitives for High-Performance Differentiable Rendering},
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author = {Samuli Laine and Janne Hellsten and Tero Karras and Yeongho Seol and Jaakko Lehtinen and Timo Aila},
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journal = {ACM Transactions on Graphics},
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year = {2020},
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volume = {39},
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number = {6}
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}
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```
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