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This paper presents a novel method to generate textures for 3D models given text prompts and 3D meshes.
Physically-based shading at disney
Walt Disney Animation Studios · 2012
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Generative adversarial networks, 2014
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling, 2017
Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T. Freeman, and Joshua B. Tenenbaum · 2017
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Text2shape: Generating shapes from natural language by learning joint embeddings, 2018
Kevin Chen, Christopher B. Choy, Manolis Savva, Angel X. Chang, Thomas Funkhouser, and Silvio Savarese · 2018
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A style-based generator architecture for generative adversarial networks, 2019
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Modular primitives for high-performance differentiable rendering
Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, and Timo Aila · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis, 2020
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Accelerating 3d deep learning with pytorch3d, 2020
Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
Earlier work this paper cites.
Text2mesh: Text-driven neural stylization for meshes, 2021
Oscar Michel, Roi Bar-On, Richard Liu, Sagie Benaim, and Rana Hanocka · 2021
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Styleclip: Text-driven manipulation of stylegan imagery, 2021
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
Earlier work this paper cites.
Vqgan-clip: Open domain image generation and editing with natural language guidance, 2022
Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff · 2022
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Objaverse: A universe of annotated 3d objects, 2022
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2022
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Kaolin: A pytorch library for accelerating 3d deep learning research
Clement Fuji Tsang, Maria Shugrina, Jean Francois Lafleche, Towaki Takikawa, Jiehan Wang, Charles Loop, Wenzheng Chen, Krishna Murthy Jatavallabhula, Edward Smith, Artem Rozantsev, Or Perel, Tianchang Shen, Jun Gao, Sanja Fidler, Gavriel State, Jason Gorski, Tommy Xiang, Jianing Li, Michael Li, and Rev Lebaredian · 2022
Cited alongside, same era.
Zero-shot text-guided object generation with dream fields, 2022
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, and Ben Poole · 2022
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Latent-nerf for shape-guided generation of 3d shapes and textures, 2022
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2022
Delta denoising score, 2023
Amir Hertz, Kfir Aberman, and Daniel Cohen-Or · 2023
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Debiasing scores and prompts of 2d diffusion for robust text-to-3d generation
Susung Hong, Donghoon Ahn, and Seungryong Kim · 2023
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3d mapping and 3d modelling market size & share analysis
Mordor Intelligence · 2023
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Magic3d: High-resolution text-to-3d content creation, 2023
Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, and Tsung-Yi Lin · 2023
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Dreambooth3d: Subject-driven text-to-3d generation, 2023
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan Barron, Yuanzhen Li, and Varun Jampani · 2023
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Texture: Text-guided texturing of 3d shapes, 2023
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Cited alongside, same era.
Clip-mesh: Generating textured meshes from text using pretrained image-text models
Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, and Tiberiu Popa · 2022
Cited alongside, same era.
Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion, 2022
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Vector-quantized image modeling with improved vqgan, 2022
Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu · 2022
Cited alongside, same era.
Panohead: Geometry-aware 3d full-head synthesis in 360
Sizhe An, Hongyi Xu, Yichun Shi, Guoxian Song, Umit Ogras, and Linjie Luo · 2023
Cited alongside, same era.
Re-imagine the negative prompt algorithm: Transform 2d diffusion into 3d, alleviate janus problem and beyond, 2023
Mohammadreza Armandpour, Ali Sadeghian, Huangjie Zheng, Amir Sadeghian, and Mingyuan Zhou · 2023
Cited alongside, same era.
Elad Richardson, Gal Metzer, Yuval Alaluf, Raja Giryes, and Daniel Cohen-Or · 2023
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Vox-e: Text-guided voxel editing of 3d objects, 2023
Etai Sella, Gal Fiebelman, Peter Hedman, and Hadar Averbuch-Elor · 2023
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Mvdream: Multi-view diffusion for 3d generation, 2023
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2023
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Mvdiffusion: Enabling holistic multi-view image generation with correspondence-aware diffusion, 2023
Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang, and Yasutaka Furukawa · 2023
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Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation, 2023
Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
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Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation
Tong Wu, Jiarui Zhang, Xiao Fu, Yuxin Wang, Liang Pan Jiawei Ren, Wayne Wu, Lei Yang, Jiaqi Wang, Chen Qian, Dahua Lin, and Ziwei Liu · 2023
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