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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Pros & Cons
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
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
Alternatives
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