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Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth data.
Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas J Guibas · 1908
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
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Grass: Generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, and Leonidas Guibas · 2017
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Deep unsupervised learning using nonequilibrium thermodynamics
Edward Smith and David Meger · 2017
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Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Learning shape templates with structured implicit functions
Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T Freeman, and Thomas Funkhouser · 2019
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Escaping plato’s cave: 3d shape from adversarial rendering
Philipp Henzler, Niloy J. Mitra, and Tobias Ritschel · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, , and Steven Lovegrove · 2019
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Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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Local deep implicit functions for 3d shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas Funkhouser · 2020
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Octree transformer: Autoregressive 3d shape generation on hierarchically structured sequences
Moritz Ibing, Gregor Kobsik, and Leif Kobbelt · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Spaghetti: Editing implicit shapes through part aware generation
Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, and Daniel Cohen-Or · 2022
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Neural template: Topology-aware reconstruction and disentangled generation of 3d meshes
Ka-Hei Hui, Ruihui Li, Jingyu Hu, and Chi-Wing Fu · 2022
Cited alongside, same era.
Neuform: Adaptive overfitting for neural shape editing
Connor Lin, Niloy Mitra, Gordon Wetzstein, Leonidas J Guibas, and Paul Guerrero · 2022
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2022
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
Cited alongside, same era.
Dsg-net: Learning disentangled structure and geometry for 3d shape generation
Jie Yang, Kaichun Mo, Yu-Kun Lai, Leonidas J Guibas, and Lin Gao · 2022
Cited alongside, same era.
Blender, 2023
Blender Foundation · 2023
Flexible isosurface extraction for gradient-based mesh optimization
Tianchang Shen, Jacob Munkberg, Jon Hasselgren, Kangxue Yin, Zian Wang, Wenzheng Chen, Zan Gojcic, Sanja Fidler, Nicholas Sharp, and Jun Gao · 2023
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Mvdream: Multi-view diffusion for 3d generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2023
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Generating part-aware editable 3d shapes without 3d supervision
Konstantinos Tertikas, Despoina Paschalidou, Boxiao Pan, Jeong Joon Park, Mikaela Angelina Uy, Ioannis Emiris, Yannis Avrithis, and Leonidas Guibas · 2023
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Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding
Le Xue, Mingfei Gao, Chen Xing, Roberto Martín-Martín, Jiajun Wu, Caiming Xiong, Ran Xu, Juan Carlos Niebles, and Silvio Savarese · 2023
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Partgen: Part-level 3d generation and reconstruction with multi-view diffusion models
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Cited alongside, same era.
Objaverse: A universe of annotated 3d objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
Shap-e: Generating conditional 3d implicit functions
Heewoo Jun and Alex Nichol · 2023
Cited alongside, same era.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
Cited alongside, same era.
Salad: Part-level latent diffusion for 3d shape generation and manipulation
Juil Koo, Seungwoo Yoo, Minh Hieu Nguyen, and Minhyuk Sung · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
Minghao Chen, Roman Shapovalov, Iro Laina, Tom Monnier, Jianyuan Wang, David Novotny, and Andrea Vedaldi · 2024
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Text-to-3d generation with bidirectional diffusion using both 2d and 3d priors
Lihe Ding, Shaocong Dong, Zhanpeng Huang, Zibin Wang, Yiyuan Zhang, Kaixiong Gong, Dan Xu, and Tianfan Xue · 2024
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Interactive3d: Create what you want by interactive 3d generation
Shaocong Dong, Lihe Ding, Zhanpeng Huang, Zibin Wang, Tianfan Xue, and Dan Xu · 2024
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Part123: part-aware 3d reconstruction from a single-view image
Anran Liu, Cheng Lin, Yuan Liu, Xiaoxiao Long, Zhiyang Dou, Hao-Xiang Guo, Ping Luo, and Wenping Wang · 2024
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Sam 2: Segment anything in images and videos
Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollár, and Christoph Feichtenhofer · 2024
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Segment any mesh: Zero-shot mesh part segmentation via lifting segment anything 2 to 3d
George Tang, William Zhao, Logan Ford, David Benhaim, and Paul Zhang · 2024
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Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation
Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, and Jun Zhu · 2024
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Unique3d: High-quality and efficient 3d mesh generation from a single image
Kailu Wu, Fangfu Liu, Zhihan Cai, Runjie Yan, Hanyang Wang, Yating Hu, Yueqi Duan, and Kaisheng Ma · 2024
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Structured 3d latents for scalable and versatile 3d generation
Jianfeng Xiang, Zelong Lv, Sicheng Xu, Yu Deng, Ruicheng Wang, Bowen Zhang, Dong Chen, Xin Tong, and Jiaolong Yang · 2024
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Clay: A controllable large-scale generative model for creating high-quality 3d assets
Longwen Zhang, Ziyu Wang, Qixuan Zhang, Qiwei Qiu, Anqi Pang, Haoran Jiang, Wei Yang, Lan Xu, and Jingyi Yu · 2024
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