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.

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Stable Video 3D was manually vetted by our editorial team and was first featured on March 19th 2024.

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Pros and 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

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

Potential baked-in lighting issue

Q&A

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.

What advancements does SV3D introduce in novel view synthesis (NVS) and 3D generation?

SV3D introduces significant advancements in novel view synthesis (NVS) and 3D generation. It achieves coherent views from any given angle with proficient generalization, enhancing pose-controllability and ensuring consistent object appearance across multiple views. This facilitates realistic and accurate 3D generations.

How does the SV3D model perform in delivering coherent views from any angle?

SV3D performs exceptionally well in delivering coherent views from any given angle. By utilizing image-to-video diffusion with camera path conditioning, it generates multi-view videos of an object. It ensures a continuous and consistent depiction of the object from any angle, enhancing its proficiency in generalization.

What makes the outputs of SV3D quality and multi-view consistent?

The outputs of SV3D are quality and multi-view consistent due to its foundational technology of Stable Video Diffusion. The diffusion model allows for the creation of multiple coherent views of a 3D object from any angle based on a single image input. The addition of camera path conditioning further amplifies view-consistency.

How does SV3D function in creating 3D videos along specified camera paths?

SV3D utilizes camera path conditioning in creating 3D videos along specified camera paths. This means that it receives information about which paths to follow when generating the videos, thereby creating a coherent and consistent multi-view 3D video from a single image input or a set of orbital views.

What features give SV3D its advanced level of performance?

The advanced level of performance in SV3D is attributed to improved generalization, accurate camera path conditioning, and consistency in multi-view rendering. Further, it efficiently delivers quality and detailed outputs, showcasing more reliable application within commercial and non-commercial scopes. It also has highly improved 3D optimization, making it superior in terms of performance.

What does the term 'orbital videos' mean in relation to SV3D?

In relation to SV3D, 'orbital videos' refer to videos generated from a single image input that provides a 360-degree view of an object, simulating the effect of orbiting around the object. The SV3D_u variant specializes in creating such videos without the need for camera conditioning.

What are the commercial conditions for using SV3D?

The commercial conditions for using SV3D involve obtaining a Stability AI Membership. With this membership, businesses and individuals can use SV3D for their commercial ventures.

Where can I find the research paper for a detailed understanding of SV3D?

The research paper for a detailed understanding of SV3D is available online. You can view it on ArXiv.