metadata

datasets:
  - allenai/objaverse
tags:
  - 3d
extra_gated_fields:
  Name: text
  Email: text
  Country: text
  Organization or Affiliation: text
  I ALLOW Stability AI to email me about new model releases: checkbox
license: mit
pipeline_tag: image-to-3d
language:
  - aa
metrics:
  - accuracy
library_name: adapter-transformers

TripoSR

TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.

Model Details

Model Description

We closely follow LRM network architecture for the model design, where TripoSR incorporates a series of technical advancements over the LRM model in terms of both data curation as well as model and training improvements. For more technical details and evaluations, please refer to our tech report.

Developed by: Stability AI, Tripo AI
Model type: Feed-forward 3D reconstruction from a single image
License: MIT
Hardware: We train TripoSR for 5 days on 22 GPU nodes each with 8 A100 40GB GPUs

Model Sources

Repository: https://github.com/VAST-AI-Research/TripoSR
Tech report: https://arxiv.org/abs/2403.02151
Demo: https://huggingface.co/spaces/stabilityai/TripoSR

Training Dataset

We use renders from the Objaverse dataset, utilizing our enhanced rendering method that more closely replicate the distribution of images found in the real world, significantly improving our model’s ability to generalize. We selected a carefully curated subset of the Objaverse dataset for the training data, which is available under the CC-BY license.

Usage

For usage instructions, please refer to our TripoSR GitHub repository
You can also try it in our gradio demo

Misuse, Malicious Use, and Out-of-Scope Use

The model should not be used to intentionally create or disseminate 3D models that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.