TripoSR
Maintainer: stabilityai
359
⛏️
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI. It closely follows the LRM network architecture with advancements in data curation and model improvements. Similar models include tripo-sr, SV3D, and StableSR, all of which focus on 3D reconstruction and generation.
Model inputs and outputs
TripoSR is a feed-forward 3D reconstruction model that takes a single image as input and generates a corresponding 3D object.
Inputs
- Single image
Outputs
- 3D object reconstruction of the input image
Capabilities
TripoSR demonstrates improved performance in 3D object reconstruction compared to previous models like LRM. By utilizing a carefully curated subset of the Objaverse dataset and enhanced rendering methods, the model is able to better generalize to real-world distributions.
What can I use it for?
The TripoSR model can be used for 3D object generation applications, such as 3D asset creation for games, visualization, and digital content production. The fast and feed-forward nature of the model makes it suitable for interactive and real-time applications. However, the model should not be used to create content that could be deemed disturbing, distressing, or offensive.
Things to try
Explore using TripoSR to generate 3D objects from single images of everyday objects, scenes, or even abstract concepts. Experiment with the model's ability to capture fine details and faithfully reconstruct the 3D structure. Additionally, consider integrating TripoSR with other tools or pipelines to enable seamless 3D content creation workflows.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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