NVlabs/nvdiffrast

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1905 stars · 243 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Nvdiffrast is a PyTorch library from NVIDIA providing high-performance, GPU-accelerated primitive operations for rasterization-based differentiable rendering, including rasterization, interpolation, texturing, and antialiasing. It is intentionally low-level, leaving camera models and material/lighting models to the user, and all operations and their gradients run on CUDA.

Use cases

• differentiable rendering for 3D reconstruction from images
• optimize 3D mesh textures and geometry via gradient descent
• train neural networks that render 3D scenes in PyTorch
• inverse graphics and 3D-aware generative model training
• fast GPU rasterization with gradients for research pipelines

When to avoid

• you need a high-level renderer with built-in camera, lighting, and material models
• you don't have an NVIDIA GPU or CUDA toolkit
• you want a pure-Python or CPU-only solution

Facets

library · maturity stable

graphics machine-learning image-processing computer-vision graphics deep-learning machine-learning windows python differentiable-rendering pytorch cuda rasterization 3d-graphics nvidia inverse-graphics gpu-accelerated linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="NVlabs/nvdiffrast")