Stable Video 3D

Stable Video 3D (SV3D) is a groundbreaking online 3D video diffusion tool that creates multi-angled views and detailed 3D meshes from a single input image. Built on the Stable Video Diffusion framework, SV3D enables novel view synthesis and efficient 3D generation, with two model variants tailored for different workflows. It supports commercial and non-commercial use, and encourages community collaboration through GitHub and social channels.

How SV3D Works

1. Provide a single image of an object.
2. SV3D generates novel multi-view representations of the object.
3. Use the generated views to create detailed 3D meshes or orbital videos.

SV3D leverages video diffusion to maintain view consistency across angles, producing realistic 3D renderings from a single input while bypassing lengthy traditional 3D modeling pipelines.

Model Variants

• SV3D_u: Generates orbital videos from single images without camera conditioning.
• SV3D_p: Supports both single images and orbital views with specified camera paths for more complex 3D video creation.

Use and Access

• Commercial use is available with a Stability AI Membership.
• Non-commercial and academic users can download model weights from Hugging Face and access the accompanying research paper.

Getting Started

• Visit the SV3D project page or GitHub repository for usage instructions, tutorials, and technical details.
• Join the community on Twitter, Instagram, LinkedIn, and Discord for updates and support.

Safety, Ethics, and Limitations

• Use SV3D responsibly and in accordance with Stability AI’s Acceptable Use Policy.
• Be mindful of limitations when generating representations of people or events; verify outputs for factual accuracy and appropriate use.

Core Features

• Single-image input to generate multi-view 3D representations
• Two variants: SV3D_u (orbital videos) and SV3D_p (camera-path 3D videos)
• High-quality 3D meshes and video outputs from minimal input
• Commercial use with Stability AI Membership; non-commercial weights on Hugging Face
• Video diffusion-based approach for improved view consistency and realism
• Accessible via GitHub, project pages, and a broad community ecosystem