658
stars
19
commits
10
repos using this model
3
linked in READMEs
Aug 9, 2024
updated
Try our new model: SF3D with several improvements such as faster generation and more game-ready assets.
TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.
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.
TripoSR for 5 days on 22 GPU nodes each with 8 A100 40GB GPUsWe 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.
For usage instructions, please refer to our TripoSR GitHub repository
You can also try it in our gradio demo
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.
18 commits
1 commits
658
stars
19
commits
10
repos using this model
3
linked in READMEs
Aug 9, 2024
updated
Try our new model: SF3D with several improvements such as faster generation and more game-ready assets.
TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.
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.
TripoSR for 5 days on 22 GPU nodes each with 8 A100 40GB GPUsWe 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.
For usage instructions, please refer to our TripoSR GitHub repository
You can also try it in our gradio demo
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.
18 commits
1 commits