Awesome Text-to-3D

The First Curation of Text-to-3D, Diffusion-to-3D works. Heavily inspired by awesome-NeRF

Recent Updates :newspaper:

• 02.04.2024 - Begin linking to project pages and codes
• 09.02.2024 - Level One Categorization
• 11.11.2023 - Added Tutorial Videos
• 05.08.2023 - Provided citations in BibTeX
• 06.07.2023 - Created initial list

Papers :scroll:

<details close> <summary>X-to-3D</summary>

• Zero-Shot Text-Guided Object Generation with Dream Fields, Ajay Jain et al., CVPR 2022 | citation | site | code

• CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation, Aditya Sanghi et al., Arxiv 2021 | citation | site | code

• PureCLIPNERF: Understanding Pure CLIP Guidance for Voxel Grid NeRF Models, Han-Hung Lee et al., Arxiv 2022 | citation | site | code

• SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation, Yen-Chi Cheng et al., CVPR 2023 | citation | site | code

• DreamFusion: Text-to-3D using 2D Diffusion, Ben Poole et al., ICLR 2023 | citation | site | code

• Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models, Jiale Xu et al., Arxiv 2022 | citation | site | code

• Novel View Synthesis with Diffusion Models, Daniel Watson et al., Arxiv 2022 | citation | site | code

• NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views, Dejia Xu et al., Arxiv 2022 | citation | site | code

• Point-E: A System for Generating 3D Point Clouds from Complex Prompts, Alex Nichol et al., Arxiv 2022 | citation | site | code

• Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures, Gal Metzer et al., Arxiv 2023 | citation | site | code

• Magic3D: High-Resolution Text-to-3D Content Creation, Chen-Hsuan Linet et al., CVPR 2023 | citation | site | code

• RealFusion: 360° Reconstruction of Any Object from a Single Image, Luke Melas-Kyriazi et al., CVPR 2023 | citation | site | code

• Monocular Depth Estimation using Diffusion Models, Saurabh Saxena et al., Arxiv 2023 | citation | site | code

• SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction, Zhizhuo Zho et al., CVPR 2023 | citation | site | code

• NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion, Jiatao Gu et al., ICML 2023 | citation | site | code

• Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation, Haochen Wang et al., CVPR 2023 | citation | site | code

• High-fidelity 3D Face Generation from Natural Language Descriptions, Menghua Wu et al., CVPR 2023 | citation | site | code

• TEXTure: Text-Guided Texturing of 3D Shapes, Elad Richardson Chen et al., SIGGRAPH 2023 | citation | site | code

• NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors, Congyue Deng et al., CVPR 2023 | citation | site | code

• DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models, Jamie Wynn et al., CVPR 2023 | citation | site | code

• 3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process, Yuhan Li et al., CVPR 2023 | citation | site | code

• DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model, Gwanghyun Kim et al., CVPR 2023 | citation | site | code

• Novel View Synthesis with Diffusion Models, Daniel Watson et al., ICLR 2023 | citation | site | code

• ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation, Zhengyi Wang et al., Arxiv 2023 | citation | site | code

• 3D-aware Image Generation using 2D Diffusion Models, Jianfeng Xiang et al., Arxiv 2023 | citation | site | code

• Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior, Junshu Tang et al., ICCV 2023 | citation | site | code

• GECCO: Geometrically-Conditioned Point Diffusion Models, Michał J. Tyszkiewicz et al., ICCV 2023 | citation | site | code

• Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond, Mohammadreza Armandpour et al., Arxiv 2023 | citation | site | code

• Generative Novel View Synthesis with 3D-Aware Diffusion Models, Eric R. Chan et al., Arxiv 2023 | citation | site | code

• Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields, Jingbo Zhang et al., Arxiv 2023 | citation | site | code

• Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors, Guocheng Qian et al., Arxiv 2023 | citation | site | code

• DreamBooth3D: Subject-Driven Text-to-3D Generation, Amit Raj et al., ICCV 2023 | citation | site | code

• Zero-1-to-3: Zero-shot One Image to 3D Object, Ruoshi Liu et al., Arxiv 2023 | citation | site | code

• ATT3D: Amortized Text-to-3D Object Synthesis, Jonathan Lorraine et al., ICCV 2023 | citation | site | code

• Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation, Zibo Zhao et al., Arxiv 2023 | citation | site | code

• Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions, Gene Chou et al., Arxiv 2023 | citation | site | code

• HiFA: High-fidelity Text-to-3D with Advanced Diffusion Guidance, Junzhe Zhu et al., Arxiv 2023 | citation | site | code

• LERF: Language Embedded Radiance Fields, Justin Kerr et al., Arxiv 2023 | citation | site | code

• 3DFuse: Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation, Junyoung Seo et al., Arxiv 2023 | citation | site | code

• MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion, Shitao Tang et al., Arxiv 2023 | citation | site | code

• One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization, Minghua Liu et al., Arxiv 2023 | citation | site | code

• TextMesh: Generation of Realistic 3D Meshes From Text Prompts, Christina Tsalicoglou Liu et al., Arxiv 2023 | citation | site | code

• Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models, Xingqian Xu et al., Arxiv 2023 | citation | site | code

• SceneScape: Text-Driven Consistent Scene Generation, Rafail Fridman et al., Arxiv 2023 | citation | site | code

• CLIP-Mesh: Generating textured meshes from text using pretrained image-text models, Nasir Khalid et al., Arxiv 2023 | citation | site | code

• Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models, Lukas Höllein et al., Arxiv 2023 | citation | site | code

• Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction, Hansheng Chen et al., Arxiv 2023 | citation | site | code

• PODIA-3D: Domain Adaptation of 3D Generative Model Across Large Domain Gap Using Pose-Preserved Text-to-Image Diffusion, Gwanghyun