Fictionarry/ER-NeRF

Health v2 · maintenance only

Adoption not part of the score

1260 stars · 143 forks observed · 2026-08-28

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

ER-NeRF is the official PyTorch implementation of an ICCV 2023 paper on region-aware Neural Radiance Fields for high-fidelity talking portrait synthesis. It generates realistic, audio-lips-synchronized 3D talking head videos from a portrait video and speech audio, with fast convergence and real-time rendering.

Use cases

• synthesize a talking head video from a single portrait video and audio
• generate lip-synced avatar videos driven by speech
• render high-fidelity 3D neural talking portraits in real time
• train a NeRF-based talking head model on custom footage
• research baseline for audio-driven portrait synthesis
• create digital human avatars for video production

When to choose

• you need high-fidelity, lip-synced talking portrait videos from short training clips
• you want real-time rendering with a small model size
• you are researching NeRF-based talking head synthesis and need a strong baseline

When to avoid

• you need a plug-and-play production tool with no GPU training
• you work on Windows or without CUDA GPUs, since it targets Ubuntu with specific PyTorch/CUDA versions
• you need 2D-only or lightweight lip-sync without 3D reconstruction

Facets

library · maturity stable

machine-learning deep-learning nlp audio-processing video-processing graphics simulation deep-learning computer-vision artificial-intelligence graphics python nerf talking-head talking-portrait audio-driven neural-rendering face-synthesis iccv-2023 research-code audio video linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Fictionarry/ER-NeRF")