yerfor/Real3DPortrait

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1091 stars · 131 forks observed · 2026-08-28

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

Official PyTorch implementation of Real3D-Portrait, an ICLR 2024 Spotlight paper for one-shot realistic 3D talking portrait synthesis. It generates high-reality talking head videos from a single source image driven by audio, using NeRF-based plane representations and audio-to-motion models.

Use cases

• generate a talking head video from a single photo and audio clip
• synthesize realistic 3D talking portraits one-shot
• animate a still portrait image with speech audio
• create talking avatar videos from one reference image
• research NeRF-based talking face generation
• train audio-to-motion and image-to-plane models for talking heads

When to choose

• you need one-shot talking portrait synthesis from a single image
• you want high video realism in audio-driven talking heads
• you need a research baseline or codebase for 3D talking face papers
• you want to train or fine-tune the full pipeline with released training code

When to avoid

• you need a production-ready, easy-to-deploy avatar API
• you lack a GPU or cannot set up a complex Conda environment with third-party models
• you only need lightweight 2D face animation without 3D reconstruction
• you want talking style control, for which MimicTalk is more suitable

Facets

library · maturity active

machine-learning deep-learning image-processing video-processing speech-recognition graphics deep-learning computer-vision artificial-intelligence python talking-face-generation nerf one-shot 3d-portrait audio-driven pytorch research-code iclr-2024 video audio linux gpu

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