# Stability-AI/stable-virtual-camera

Stable Virtual Camera: Generative View Synthesis with Diffusion Models

Repository: https://github.com/Stability-AI/stable-virtual-camera
Canonical: https://ross.abutalabs.com/products/stable-virtual-camera
Homepage: https://stable-virtual-camera.github.io
Language: Python
License: NOASSERTION
License Family: other
Topics: diffusion-model, image-to-video, novel-view-synthesis, stable-virtual-camera
Last push: 2026-03-03T06:48:30+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 70, release rhythm 40, longevity 40
- inputs: {"age_days": 560, "days_push": 183, "days_rel": 538, "gap_med": 0, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1652, forks 125 (observed 2026-08-28T04:05:17.074727+00:00)

## What it is
Stable Virtual Camera (SEVA) is a generalist diffusion model for novel view synthesis that generates 3D-consistent views of a scene from any number of input images and target camera trajectories. It is released as a Python codebase with pretrained 1.3B-parameter checkpoints and a Gradio demo for image-to-video generation with camera control.

## Use cases
- generate novel views of a scene from a single image
- create orbit or spiral camera trajectory videos from photos
- synthesize 3D-consistent video from image inputs with diffusion models
- interpolate between two views of a scene
- explore 3D scenes without explicit 3D reconstruction
- run novel view synthesis research benchmarks

## When to choose
- you need 3D-consistent novel views or camera-trajectory videos from one or few images
- you want a pretrained generalist NVS diffusion model without building explicit 3D representations
- you need keyframe-based camera trajectory control for creative video generation

## When to avoid
- you need real-time rendering or guaranteed geometric accuracy from true 3D reconstruction
- you lack a GPU or cannot accept a non-commercial-style custom license (NOASSERTION)
- your task is standard text-to-video generation without camera control

## Facets
- artifact type: library
- maturity: active
- function: image-processing, video-processing, machine-learning, deep-learning
- domain: computer-vision, artificial-intelligence, graphics, deep-learning
- platform: python
- tags: diffusion-model, novel-view-synthesis, image-to-video, 3d-consistency, camera-trajectory, generative-ai, linux, gpu

## Member repositories
- Stability-AI/stable-virtual-camera (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:17.074727+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:44:59.273063+00:00, confidence not recorded.
  - readme: https://github.com/Stability-AI/stable-virtual-camera (fetched 2026-08-28T04:05:17.074727+00:00, sha 5b455f32b4ad)
  - homepage: https://stable-virtual-camera.github.io (fetched 2026-08-29T11:18:07.650239+00:00, sha eff65acdb3b5)
- Data as of 2026-08-30T08:39:29.467469+00:00.