base on Official implementation of "LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching" # [CVPR 2024 Highlight (11.9%)] LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching [Yixun Liang](https://yixunliang.github.io/)$^{\color{red}{\*}}$ [Xin Yang](https://abnervictor.github.io/2023/06/12/Academic-Self-Intro.html)$^{\color{red}{\*}}$, [Jiantao Lin](https://ltt-o.github.io/), [Haodong Li](https://haodong-li.com/), [Xiaogang Xu](https://xiaogang00.github.io), [Yingcong Chen](https://www.yingcong.me)$^{\**}$ $\color{red}{\*}$: Equal contribution. \**: Corresponding author. [Paper PDF (Arxiv)](https://arxiv.org/abs/2311.11284) | [Project Page (Coming Soon)]() | [Gradio Demo](resources/Gradio_Demo.md) The paper is now accepted to CVPR 2024 as poster (highlight, 11.9%). --- <div align=center> <img src="resources/gif/demo-1.gif" width="47.5%"/><img src="resources/gif/demo-2.gif" width="47.5%"/> Note: we compress these motion pictures for faster previewing. </div> <div align=center> <img src="resources/teaser.jpg" width="95%"/> Examples of text-to-3D content creations with our framework, the *LucidDreamer*, within **~35mins** on A100. </div> ## :tv: Video </div> <div align=center> [](https://www.youtube.com/watch?v=zToxGi_hNWs "LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching") Please click to watch the 3-minute video introduction of our project. </div> ## 🎏 Abstract We present a text-to-3D generation framework, named the *LucidDreamer*, to distill high-fidelity textures and shapes from pretrained 2D diffusion models. <details><summary>CLICK for the full abstract</summary> > The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D generation have shown promise, they often fall short in rendering detailed and high-quality 3D models. This problem is especially prevalent as many methods base themselves on Score Distillation Sampling (SDS). This paper identifies a notable deficiency in SDS, that it brings inconsistent and low-quality updating direction for the 3D model, causing the over-smoothing effect. To address this, we propose a novel approach called Interval Score Matching (ISM). ISM employs deterministic diffusing trajectories and utilizes interval-based score matching to counteract over-smoothing. Furthermore, we incorporate 3D Gaussian Splatting into our text-to-3D generation pipeline. Extensive experiments show that our model largely outperforms the state-of-the-art in quality and training efficiency. </details> ## 🔧 Training Instructions Our code is now released! Please refer to this [**link**](resources/Training_Instructions.md) for detailed training instructions. ## 🤗 Gradio Demo We are currently building an online demo of LucidDreamer with Gradio, you can check it out by clicking this [link](https://huggingface.co/spaces/haodongli/LucidDreamer). It is still under development, and the service might not be available from time to time. ## 🚧 Todo - [x] Release the basic training codes - [x] Release the guidance documents - [ ] Release the training codes for more applications ## 📍 Citation ``` @article{EnVision2023luciddreamer, title={Luciddreamer: Towards high-fidelity text-to-3d generation via interval score matching}, author={Liang, Yixun and Yang, Xin and Lin, Jiantao and Li, Haodong and Xu, Xiaogang and Chen, Yingcong}, journal={arXiv preprint arXiv:2311.11284}, year={2023} } ``` ## Acknowledgement This work is built on many amazing research works and open-source projects: - [gaussian-splatting](https://github.com/graphdeco-inria/gaussian-splatting) and [diff-gaussian-rasterization](https://github.com/graphdeco-inria/diff-gaussian-rasterization) - [Stable-Dreamfusion](https://github.com/ashawkey/stable-dreamfusion) - [Point-E](https://github.com/openai/point-e) Thanks for their excellent work and great contribution to 3D generation area. ", Assign "at most 3 tags" to the expected json: {"id":"5405","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"