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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.
A growing curation of Text-to-3D, Diffusion-to-3D works.
| Date | Stars |
|---|---|
| 2026-07-24 | 593 |
| 2026-07-25 | 593 |
| 2026-07-28 | 593 |
| 2026-07-30 | 593 |
| 2026-08-06 | 593 |
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# Awesome Text-to-3D [](https://github.com/sindresorhus/awesome) []() [](https://makeapullrequest.com) The first curated list of Text-to-3D and Diffusion-to-3D research, heavily inspired by [awesome-NeRF](https://github.com/awesome-NeRF/awesome-NeRF). This README is intended to work as a fast research index: - grouped by task and content type - linked to BibTeX, project pages, and code when available - updated incrementally as new papers and resources appear ## Overview - Core categories: X-to-3D, 3D Editing, Avatars, Dynamic Content, World Models - Reference sections: Datasets, Frameworks & Projects, Tutorial Videos - Link legend: `citation` points to BibTeX, `site` points to the project page, `code` points to the implementation when public ## Navigation - 📚 [Papers](#papers-scroll) - 🧊 [X-to-3D](#x-to-3d) - ✏️ [3D Editing, Decomposition & Stylization](#3d-editing-decomposition--stylization) - 🧍 [Avatar Generation and Manupilation](#avatar-generation-and-manupilation) - 🎞️ [Dynamic Content Generation](#dynamic-content-generation) - 🌍 [World Models](#world-models) - 💾 [Datasets](#datasets-floppy_disk) - 🛠️ [Frameworks & Projects](#frameworks--projects-desktop_computer) - 📺 [Tutorial Videos](#tutorial-videos-tv) - ✅ [TODO](#todo) ## Papers :scroll: <a id="x-to-3d"></a> <details close> <summary>X-to-3D</summary> - [Zero-Shot Text-Guided Object Generation with Dream Fields](https://arxiv.org/abs/2112.01455), Ajay Jain et al., CVPR 2022 | [citation](./references/citations.bib#L1-L6) | [site](https://ajayj.com/dreamfields) | [code](https://github.com/google-research/google-research/tree/master/dreamfields) - [CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation](https://arxiv.org/abs/2110.02624), Aditya Sanghi et al., Arxiv 2021 | [citation](./references/citations.bib#L8-L13) | [site]() | [code](https://github.com/AutodeskAILab/Clip-Forge) - [PureCLIPNERF: Understanding Pure CLIP Guidance for Voxel Grid NeRF Models](https://arxiv.org/abs/2209.15172), Han-Hung Lee et al., Arxiv 2022 | [citation](./references/citations.bib#L29-L34) | [site](https://hanhung.github.io/PureCLIPNeRF/) | [code](https://github.com/hanhung/PureCLIPNeRF) - [SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation](https://arxiv.org/abs/2212.04493), Yen-Chi Cheng et al., CVPR 2023 | [citation](./references/citations.bib#L43-L48) | [site](https://yccyenchicheng.github.io/SDFusion/) | [code](https://github.com/yccyenchicheng/SDFusion) - [DreamFusion: Text-to-3D using 2D Diffusion](https://dreamfusion3d.github.io/), Ben Poole et al., ICLR 2023 | [citation](./references/citations.bib#L57-L62) | [site](https://dreamfusion3d.github.io/) | [code]() - [Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models](https://arxiv.org/abs/2212.14704), Jiale Xu et al., Arxiv 2022 | [citation](./references/citations.bib#L64-L69) | [site](https://bluestyle97.github.io/dream3d/) | [code]() - [Novel View Synthesis with Diffusion Models](https://arxiv.org/abs/2210.04628), Daniel Watson et al., Arxiv 2022 | [citation](./references/citations.bib#L78-L83) | [site](https://3d-diffusion.github.io/) | [code]() - [NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views](https://arxiv.org/abs/2211.16431), Dejia Xu et al., Arxiv 2022 | [citation](./references/citations.bib#L85-L90) | [site](https://vita-group.github.io/NeuralLift-360/) | [code](https://github.com/VITA-Group/NeuralLift-360) - [Point-E: A System for Generating 3D Point Clouds from Complex Prompts](https://arxiv.org/abs/2212.08751), Alex Nichol et al., Arxiv 2022 | [citation](./references/citations.bib#L92-L97) | [site](https://openai.com/index/point-e/) | [code](h
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Mishan Aliev · BayesGroup · Russia
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3808da3e45db3a24, topic:text-to-3d, readme:avatar generation, name:text-to-3d
matched fp:3808da3e45db3a24, topic:nerf