autonomousvision/giraffe

Health v2 · maintenance only

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1238 stars · 156 forks observed · 2026-08-28

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

Official PyTorch implementation of GIRAFFE, a CVPR 2021 (oral, best paper award) generative model that represents scenes as compositional generative neural feature fields. It combines a compositional 3D scene representation with neural rendering to enable controllable, photorealistic image synthesis from unposed image collections.

Use cases

• generate controllable images of scenes with movable objects
• train a GAN with compositional 3D scene representation
• render pre-trained models on cars or CelebA-HQ datasets
• translate and rotate objects in generated scenes
• change camera pose in generated images
• research NeRF-style implicit neural scene representations
• reproduce CVPR 2021 paper results

When to choose

• you need controllable image synthesis with disentangled objects, shapes, and appearances
• you are researching compositional 3D-aware generative models or NeRF variants
• you want to render or fine-tune provided pre-trained models on standard datasets

When to avoid

• you need a production-ready image generation service rather than research code
• you lack a GPU or cannot manage the conda environment dependencies
• you need 2D-only image generation without 3D scene control
• the project is research code from 2021 and may need adaptation for modern frameworks

Facets

library · maturity maintenance

machine-learning deep-learning image-processing graphics computer-vision deep-learning machine-learning graphics python gan nerf generative-model 3d-scene-representation controllable-image-synthesis cvpr2021 research-code linux gpu

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