Real3D
Model Details:
Model Description:
We use the model architecture provided by TripoSR, which is a Transformer model for 2D-to-3D mapping built on LRM.
We scale it further on in-the-wild image collections by enabling unsupervised self-training and automatric data curation.
- Developed by: Hanwen Jiang
- License: MIT
- Hardware: We train Real3D on 1 node (8GPU) with equivalent batch size of 80 for 5-6 days.
Model Sources:
- Paper: https://arxiv.org/abs/2406.08479
- Project: https://hwjiang1510.github.io/Real3D/
- Code for training and evaluation: https://github.com/hwjiang1510/Real3D
Training Data: Real3D is jointly trained on synthetic data (Objaverse) and in-the-wild image collections. The former prevents training divergence, the latter introduces new knowldege from a broader distribution of real images. We use Objaverse renderings from Zero-1-to-3 and GObjaverse. The in the wild images are from ImageNet, OpenImages, etc.
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.
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