liuyuan-pal/SyncDreamer

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1045 stars · 50 forks observed · 2026-10-21

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

SyncDreamer is a synchronized multiview diffusion model that generates multiview-consistent images from a single-view image, released with inference, training, and evaluation code plus pretrained checkpoints. It enables downstream 3D reconstruction with NeuS or NeRF without SDS loss, supporting tasks like novel-view synthesis, text-to-3D, and image-to-3D.

Use cases

• generate consistent views of an object from one photo
• reconstruct a 3D model from a single image
• turn sketches or paintings into 3D models
• novel view synthesis from a single image
• create multiview training data for NeRF or NeuS
• image-to-3D asset generation for games

When to choose

• you need geometry- and color-consistent multiview images from one input image
• you want to feed generated views directly into NeRF/NeuS reconstruction without SDS optimization
• you want a research-grade model with training code and pretrained weights
• you have a GPU (10GB+ VRAM) for inference

When to avoid

• you need real-time or CPU-only inference
• you want a polished end-user application rather than research code
• you cannot supply an elevation angle or foreground mask for the input image
• you need a pretrained model without elevation input, which is not yet released

Facets

library · maturity active

machine-learning deep-learning image-processing computer-vision computer-vision image-processing graphics artificial-intelligence python diffusion-models novel-view-synthesis multiview-generation 3d-reconstruction image-to-3d research-code gpu linux

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