Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Official repo for paper "Structured 3D Latents for Scalable and Versatile 3D Generation" (CVPR'25 Spotlight).
| Date | Stars |
|---|---|
| 2026-07-24 | 13277 |
| 2026-07-25 | 13286 |
| 2026-07-28 | 13286 |
| 2026-07-30 | 13286 |
| 2026-08-06 | 13286 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<img src="assets/logo.webp" width="100%" align="center"> <h1 align="center">Structured 3D Latents<br>for Scalable and Versatile 3D Generation</h1> <p align="center"><a href="https://arxiv.org/abs/2412.01506"><img src='https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv&logoColor=white' alt='arXiv'></a> <a href='https://microsoft.github.io/TRELLIS/'><img src='https://img.shields.io/badge/Project_Page-Website-green?logo=googlechrome&logoColor=white' alt='Project Page'></a> <a href='https://huggingface.co/spaces/Microsoft/TRELLIS'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Live_Demo-blue'></a> </p> <p align="center"><img src="assets/teaser.png" width="100%"></p> <span style="font-size: 16px; font-weight: 600;">T</span><span style="font-size: 12px; font-weight: 700;">RELLIS</span> is a large 3D asset generation model. It takes in text or image prompts and generates high-quality 3D assets in various formats, such as Radiance Fields, 3D Gaussians, and meshes. The cornerstone of <span style="font-size: 16px; font-weight: 600;">T</span><span style="font-size: 12px; font-weight: 700;">RELLIS</span> is a unified Structured LATent (<span style="font-size: 16px; font-weight: 600;">SL</span><span style="font-size: 12px; font-weight: 700;">AT</span>) representation that allows decoding to different output formats and Rectified Flow Transformers tailored for <span style="font-size: 16px; font-weight: 600;">SL</span><span style="font-size: 12px; font-weight: 700;">AT</span> as the powerful backbones. We provide large-scale pre-trained models with up to 2 billion parameters on a large 3D asset dataset of 500K diverse objects. <span style="font-size: 16px; font-weight: 600;">T</span><span style="font-size: 12px; font-weight: 700;">RELLIS</span> significantly surpasses existing methods, including recent ones at similar scales, and showcases flexible output format selection and local 3D editing capabilities which were not offered by previous models. ***Check out our [Project Page](https://microsoft.github.io/TRELLIS/) for more videos and interactive demos!*** <!-- Features --> ## 🌟 Features - **High Quality**: It produces diverse 3D assets at high quality with intricate shape and texture details. - **Versatility**: It takes text or image prompts and can generate various final 3D representations including but not limited to *Radiance Fields*, *3D Gaussians*, and *meshes*, accommodating diverse downstream requirements. - **Flexible Editing**: It allows for easy editings of generated 3D assets, such as generating variants of the same object or local editing of the 3D asset. <!-- Updates --> ## ⏩ Updates **03/25/2025** - Release training code. - Release **TRELLIS-text** models and asset variants generation. - Examples are provided as [example_text.py](example_text.py) and [example_variant.py](example_variant.py). - Gradio demo is provided as [app_text.py](app_text.py). - *Note: It is always recommended to do text to 3D generation by first generating images using text-to-image models and then using TRELLIS-image models for 3D generation. Text-conditioned models are less creative and detailed due to data limitations.* **12/26/2024** - Release [**TRELLIS-500K**](https://github.com/microsoft/TRELLIS#-dataset) dataset and toolkits for data preparation. **12/18/2024** - Implementation of multi-image conditioning for **TRELLIS-image** model. ([#7](https://github.com/microsoft/TRELLIS/issues/7)). This is based on tuning-free algorithm without training a specialized model, so it may not give the best results for all input images. - Add Gaussian export in `app.py` and `example.py`. ([#40](https://github.com/microsoft/TRELLIS/issues/40)) <!-- Installation --> ## 📦 Installation ### Prerequisites - **System**: The code is currently tested only on **Linux**. For windows setup, you may refer to [#3](https://github.com/microsoft/TRELLIS/issues/3) (not fully tested). - **Hardware**: An NVIDIA GPU with at least 16GB of mem
Excerpt of 21,977 characters
Read on GitHub
12
6
Microsoft Open Source · Microsoft · United States
5
4
1
Bowen Zhang · University of Science and Technology of China · United States
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:261303481926a29b, topic:text-to-3d, readme:text-to-3d, desc:3d generation