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We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control.
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Occupancy Networks: Learning 3D Reconstruction in Function Space
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Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire, and Sanja Fidler · 2020
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NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
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Accelerating 3d deep learning with pytorch3d
Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
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Shangzhe Wu, Christian Rupprecht, and Andrea Vedaldi · 2020
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NeRD: Neural Reflectance Decomposition from Image Collections
Mark Boss, Raphael Braun, Varun Jampani, Jonathan T. Barron, Ce Liu, and Hendrik P.A. Lensch · 2021
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Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan T. Barron, and Hendrik P. A. Lensch · 2021
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UNISURF: unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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NeuS: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
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NeRFactor: neural factorization of shape and reflectance under an unknown illumination
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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild
Jason Y. Zhang, Gengshan Yang, Shubham Tulsiani, and Deva Ramanan · 2021
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PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting
Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, and Noah Snavely · 2021
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Neural rgb-d surface reconstruction
Dejan Azinović, Ricardo Martin-Brualla, Dan B Goldman, Matthias Nießner, and Justus Thies · 2022
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Efficient geometry-aware 3D generative adversarial networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J. Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, and Gordon Wetzstein · 2022
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TensoRF: Tensorial radiance fields
Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022
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Improving neural implicit surfaces geometry with patch warping
François Darmon, Bénédicte Bascle, Jean-Clément Devaux, Pascal Monasse, and Mathieu Aubry · 2022
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Google Scanned Objects: A high-quality dataset of 3D scanned household items
Laura Downs, Anthony Francis, Nate Koenig, Brandon Kinman, Ryan Hickman, Krista Reymann, Thomas B. McHugh, and Vincent Vanhoucke · 2022
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Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction
Qiancheng Fu, Qingshan Xu, Yew-Soon Ong, and Wenbing Tao · 2022
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Differentiable Stereopsis: Meshes from multiple views using differentiable rendering
Shubham Goel, Georgia Gkioxari, and Jitendra Malik · 2022
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Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising
Jon Hasselgren, Nikolai Hofmann, and Jacob Munkberg · 2022
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Magic3D: High-resolution text-to-3D content creation
Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, and Tsung-Yi Lin · 2022
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Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency
Tom Monnier, Matthew Fisher, Alexei A. Efros, and Mathieu Aubry · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Extracting Triangular 3D Models, Materials, and Lighting From Images
Jacob Munkberg, Wenzheng Chen, Jon Hasselgren, Alex Evans, Tianchang Shen, Thomas Muller, Jun Gao, and Sanja Fidler · 2022
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Point-E: A system for generating 3D point clouds from complex prompts
Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen · 2022
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3D neural field generation using triplane diffusion
J. Ryan Shue, Eric Ryan Chan, Ryan Po, Zachary Ankner, Jiajun Wu, and Gordon Wetzstein · 2022
DreamGaussian: Generative gaussian splatting for efficient 3D content creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, and Gang Zeng · 2023
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Make-It-3D: High-fidelity 3d creation from A single image with diffusion prior
Junshu Tang, Tengfei Wang, Bo Zhang, Ting Zhang, Ran Yi, Lizhuang Ma, and Dong Chen · 2023
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Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, and Greg Shakhnarovich · 2023
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Rodin: A generative model for sculpting 3D digital avatars using diffusion
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, and Baining Guo · 2023
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ProlificDreamer: High-fidelity and diverse text-to-3D generation with variational score distillation
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Xatlas: Mesh parameterization / uv unwrapping library, 2022
Jonathan Young · 2022
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Generative novel view synthesis with 3D-aware diffusion models
Eric R. Chan, Koki Nagano, Matthew A. Chan, Alexander W. Bergman, Jeong Joon Park, Axel Levy, Miika Aittala, Shalini De Mello, Tero Karras, and Gordon Wetzstein · 2023
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Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
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Cascade-Zero123: One image to highly consistent 3D with self-prompted nearby views
Yabo Chen, Jiemin Fang, Yuyang Huang, Taoran Yi, Xiaopeng Zhang, Lingxi Xie, Xinggang Wang, Wenrui Dai, Hongkai Xiong, and Qi Tian · 2023
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Text-to-3D using Gaussian splatting
Zilong Chen, Feng Wang, and Huaping Liu · 2023
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Emu: Enhancing image generation models using photogenic needles in a haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam S. Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, and Devi Parikh · 2023
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Antoine Guédon and Vincent Lepetit · 2023
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Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
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Consistent123: Improve consistency for one image to 3D object synthesis
Haohan Weng, Tianyu Yang, Jianan Wang, Yu Li, Tong Zhang, C. L. Philip Chen, and Lei Zhang · 2023
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ReconFusion: 3D Reconstruction with Diffusion Priors
Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, and Aleksander Holynski · 2023
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MATLABER: Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR
Xudong Xu, Zhaoyang Lyu, Xingang Pan, and Bo Dai · 2023
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ConsistNet: Enforcing 3D consistency for multi-view images diffusion
Jiayu Yang, Ziang Cheng, Yunfei Duan, Pan Ji, and Hongdong Li · 2023
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DreamComposer: Controllable 3D object generation via multi-view conditions
Yunhan Yang, Yukun Huang, Xiaoyang Wu, Yuan-Chen Guo, Song-Hai Zhang, Hengshuang Zhao, Tong He, and Xihui Liu · 2023
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Mosaic-SDF for 3D generative models
Lior Yariv, Omri Puny, Natalia Neverova, Oran Gafni, and Yaron Lipman · 2023
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GaussianDreamer: Fast generation from text to 3D gaussian splatting with point cloud priors
Taoran Yi, Jiemin Fang, Guanjun Wu, Lingxi Xie, Xiaopeng Zhang, Wenyu Liu, Qi Tian, and Xinggang Wang · 2023
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HiFi-123: Towards high-fidelity one image to 3D content generation
Wangbo Yu, Li Yuan, Yan-Pei Cao, Xiangjun Gao, Xiaoyu Li, Long Quan, Ying Shan, and Yonghong Tian · 2023
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HiFA: High-fidelity text-to-3D with advanced diffusion guidance
Junzhe Zhu and Peiye Zhuang · 2023
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Zi-Xin Zou, Zhipeng Yu, Yuan-Chen Guo, Yangguang Li, Ding Liang, Yan-Pei Cao, and Song-Hai Zhang · 2023
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Lightplane: Highly-scalable components for neural 3d fields
Ang Cao, Justin Johnson, Andrea Vedaldi, and David Novotny · 2024
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V3D: Video diffusion models are effective 3D generators
Zilong Chen, Yikai Wang, Feng Wang, Zhengyi Wang, and Huaping Liu · 2024
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CAT3D: Create Anything in 3D with Multi-View Diffusion Models
Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul Srinivasan, Jonathan T. Barron, and Ben Poole · 2024
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ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models
Lukas Höllein, Aljaž Božič, Norman Müller, David Novotny, Hung-Yu Tseng, Christian Richardt, Michael Zollhöfer, and Matthias Nießner · 2024
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LRM: Large reconstruction model for single image to 3D
Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, and Hao Tan · 2024
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Vfusion3d: Learning scalable 3d generative models from video diffusion models
Philip Torr Junlin Han, Filippos Kokkinos · 2024
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Multi-view image prompted multi-view diffusion for improved 3D generation
Seungwook Kim, Yichun Shi, Kejie Li, Minsu Cho, and Peng Wang · 2024
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Instant3D: Fast text-to-3D with sparse-view generation and large reconstruction model
Jiahao Li, Hao Tan, Kai Zhang, Zexiang Xu, Fujun Luan, Yinghao Xu, Yicong Hong, Kalyan Sunkavalli, Greg Shakhnarovich, and Sai Bi · 2024
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IM-3D: Iterative multiview diffusion and reconstruction for high-quality 3D generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Natalia Neverova, Andrea Vedaldi, Oran Gafni, and Filippos Kokkinos · 2024
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HexaGen3D: Stablediffusion is just one step away from fast and diverse text-to-3D generation
Antoine Mercier, Ramin Nakhli, Mahesh Reddy, and Rajeev Yasarla · 2024
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MVDream: Multi-view diffusion for 3D generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2024
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LGM: Large multi-view Gaussian model for high-resolution 3D content creation
Jiaxiang Tang, Zhaoxi Chen, Xiaokang Chen, Tengfei Wang, Gang Zeng, and Ziwei Liu · 2024
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MVDiffusion++: A dense high-resolution multi-view diffusion model for single or sparse-view 3d object reconstruction
Shitao Tang, Jiacheng Chen, Dilin Wang, Chengzhou Tang, Fuyang Zhang, Yuchen Fan, Vikas Chandra, Yasutaka Furukawa, and Rakesh Ranjan · 2024
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TripoSR: fast 3D object reconstruction from a single image
Dmitry Tochilkin, David Pankratz, Zexiang Liu, Zixuan Huang, Adam Letts, Yangguang Li, Ding Liang, Christian Laforte, Varun Jampani, and Yan-Pei Cao · 2024
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ImageDream: Image-prompt multi-view diffusion for 3D generation
Peng Wang and Yichun Shi · 2024
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CRM: Single image to 3D textured mesh with convolutional reconstruction model
Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, and Jun Zhu · 2024
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MeshLRM: large reconstruction model for high-quality mesh
Xinyue Wei, Kai Zhang, Sai Bi, Hao Tan, Fujun Luan, Valentin Deschaintre, Kalyan Sunkavalli, Hao Su, and Zexiang Xu · 2024
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LATTE3D: Large-scale amortized text-to-enhanced3D synthesis
Kevin Xie, Jonathan Lorraine, Tianshi Cao, Jun Gao, James Lucas, Antonio Torralba, Sanja Fidler, and Xiaohui Zeng · 2024
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InstantMesh: efficient 3D mesh generation from a single image with sparse-view large reconstruction models
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GRM: Large gaussian reconstruction model for efficient 3D reconstruction and generation
Yinghao Xu, Zifan Shi, Wang Yifan, Hansheng Chen, Ceyuan Yang, Sida Peng, Yujun Shen, and Gordon Wetzstein · 2024
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DMV3D: Denoising multi-view diffusion using 3D large reconstruction model
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GALA3D: Towards text-to-3D complex scene generation via layout-guided generative gaussian splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong, Jinlin He, Zhiwei Lin, Yongtao Wang, Deqing Sun, and Ming-Hsuan Yang · 2024
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