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3D videos

Stable Video 3D ✓

Generate high-quality 3D views from single images

Source rating 4.3 (4) 3.9k views 47 saves Paid
API Novel View Synthesis 3D Technology
More categories (4)
3D Video Creation Multi-view Consistency View Consistency 3D videos
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from $9/mo

Verdict

A quick read before you dig into the full page.

Best if
Generate high-quality 3D views from single images
Skip if
Two variant complexity
Pick this when
Improved quality output

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Overview

Stable Video 3D (SV3D) is a revolutionary generative model that fuels advancements in the field of 3D technology. A product of Stability AI, SV3D draws upon the versatility and foundation of Stable Video Diffusion to offer greatly improved quality and multi-view consistency.

The tool operates with a more advanced level of performance compared to its predecessor, Stable Zero123 and other open source alternatives such as Zero123-XL.

The SV3D model comes in two variants. The SV3D_u generates orbital videos from single image inputs without camera conditioning, while the SV3D_p boats a higher functionality by accommodating both single images and orbital views, hence enabling the creation of 3D video along specified camera paths.

Adapting the Stable Video Diffusion image-to-video diffusion model with the addition of camera path conditioning, the tool is designed to generate multi-view videos of an object.

This technique provides major benefits in terms of generalization and view-consistency of generated outputs. Therefore, SV3D can be used to output quality 3D meshes from single image inputs.

Both commercial and non-commercial usage is supported. The model weights are downloadable on Hugging Face and a research paper is available for detailed understanding.

Stable Video 3D also introduces significant advancements in novel view synthesis (NVS) and 3D generation, delivering coherent views from any given angle with proficient generalization.

Stable Video 3D website

Access & connections

Where you can use Stable Video 3D.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Image

Output

  • 3D
  • API

Pros & cons

Pros

  • Improved quality output
  • Offers multi-view consistency
  • Two variants for functionalities
  • Generates orbital videos
  • Inputs: single or orbital images
  • 3D video creation
  • Video with specified camera paths
  • Delivers coherent views
Show 38 more
  • Proficient generalization
  • Suitable for any given angle
  • Outputs quality 3D meshes
  • Can be used commercially
  • Supports non-commercial use
  • Model weights available for download
  • Advancements in 3D generation
  • Improves novel view synthesis
  • Flexible application (single images to video)
  • Image-to-video diffusion model diffuseness
  • Outperforms similar open source alternatives
  • Accommodates specified camera paths
  • Supports single image inputs
  • Offers detailed technical reports
  • Documented in a research paper
  • Outputs are view-consistent
  • Provides major benefits in generalization
  • Enables the creation of arbitrary orbits
  • Offers enhanced pose-controllability
  • Ensures consistent object appearance
  • More detailed and faithful outputs
  • Superior multi-view consistency compared to competitors
  • Optimized 3D Neural Radiance Fields
  • Improved 3D mesh qualities
  • Disentangled illumination model
  • Joint optimization of 3D shape and texture
  • Masked score distillation sampling loss
  • Reduces baked-in lighting issues
  • Increased 3D quality in non-visible regions
  • Stable Video Diffusion
  • Enhances realistic and accurate 3D generation
  • Membership for commercial use available
  • Model weights downloadable on Hugging Face
  • Downloadable research paper for deeper understanding
  • Two distinct versions (SV3D_u and SV3D_p)
  • Availability of Stable Video 3D resources online
  • Continue quality improvements over predecessors
  • Active online presence on various platforms

Cons

  • Two variant complexity
  • Dependent on camera conditioning
  • Requires single image input
  • Need for downloaded model weights
  • Reliance on Hugging Face
  • Separate use for commercial/non-commercial
  • Diffusion model complexities
  • Dependency on 3D meshes
Show 1 more
  • Potential baked-in lighting issue

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Releases 1

Initial release March 18, 2024 Current
Initial release of Stable Video 3D.

FAQ 12

What is Stable Video 3D (SV3D)?
Stable Video 3D (SV3D) is a generative model developed by Stability AI. It utilizes the foundation of Stable Video Diffusion to generate quality 3D videos. It operates with a high level of performance and comes in two variants, SV3D_u and SV3D_p. The former generates orbital videos from single image inputs without camera conditioning, while the latter accommodates both single images and orbital views, enabling the creation of 3D video along specified camera paths.
How does SV3D advance the field of 3D technology?
SV3D advances the field of 3D technology by introducing novel advancements in 3D generation and novel view synthesis (NVS). It utilizes a diffusion model that permits multi-view videos of an object, from a single image. This results in greater generalization and view-consistency in its outputs. Additionally, it can reliably output quality 3D meshes from single image inputs, marking a significant shift in the field of 3D technology.
What improvements over previous models does SV3D offer?
SV3D offers a major improvement over previous models in quality and multi-view consistency. It operates with a more advanced level of performance compared to its predecessor, Stable Zero123. By using a diffusion model with camera path conditioning, SV3D is able to generate multi-view videos of an object, improving terms of generalization and view-consistency of the generated outputs.
What are the different variants of SV3D and how do they function?
SV3D comes in two variants, SV3D_u and SV3D_p. The SV3D_u generates orbital videos based on single image inputs without camera conditioning, creating a novel view from a single angle. On the other hand, SV3D_p extends its functionality by accepting both single images and orbital views. It allows for the creation of 3D video along specified camera paths, providing a comprehensive 3D view of an object from multiple angles.
What is Stable Video Diffusion and how does SV3D utilize it?
Stable Video Diffusion is a versatile model developed by Stability AI to generate quality videos. It forms the backbone of SV3D. The Stable Video Diffusion image-to-video diffusion model is adapted by SV3D, with the addition of camera path conditioning. This technique enables SV3D to generate multi-view videos of an object, offering major benefits in terms of generalization and view-consistency of generated outputs.
In what ways does SV3D improve on open source alternatives such as Zero123-XL?
SV3D improves on open source alternatives such as Zero123-XL by offering greatly improved quality and multi-view consistency. It offers an advanced level of performance and comes with additional features like camera path conditioning, which allows for the creation of 3D video along specified camera paths. It also has a better generalization capability and generates more consistent views compared to these alternatives.
How does SV3D create 3D videos from single images and/or orbital views?
SV3D creates 3D videos from single images or orbital views by using a technique called image-to-video diffusion. By integrating camera path conditioning, the model generates multi-view videos of an object from single image inputs. In the case of the SV3D_p variant, it has the additional feature of accepting orbital views, which enables the creation of 3D videos along specified paths.
What is the role of camera path conditioning in SV3D?
Camera path conditioning in SV3D is used to guide the model in generating multi-view videos of an object. It lets the model know the specific paths along which to generate the 3D videos, hence ensuring greater view-consistency in the generated outputs.
What benefits does SV3D's image-to-video diffusion model offer in terms of generalization and view-consistency?
SV3D's image-to-video diffusion model offers major benefits concerning the generalization and view-consistency of generated outputs. As it generates videos based on a single image input, it has to generalize the 3D appearance of the object. Also, due to the application of camera path conditioning in the model, the generated outputs maintain view-consistency across the specified paths.
How can SV3D be used for 3D mesh generation from single image inputs?
SV3D can be used for 3D mesh generation from single image inputs due to its image-to-video diffusion model. By using novel views generated from a single image input and implementing techniques such as camera path conditioning and disentangled illumination optimization, SV3D can output quality 3D meshes reliably.
Does SV3D support both commercial and non-commercial usage?
Yes, SV3D supports both commercial and non-commercial usage. For commercial purposes, users need to have a Stability AI Membership. Non-commercial users can download the model weights for free.
Where can the model weights for SV3D be downloaded?
The model weights for SV3D can be downloaded from Hugging Face.
Stable Video 3D from $9/mo
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