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Text- or image-to-3D generators and 3D scanners can now produce 3D assets with high-quality shapes and textures.
Pascal visual object classes challenge
D. Larlus, G. Dorko, D. Jurie, and B. Triggs · 2006
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
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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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Occupancy Networks: Learning 3D reconstruction in function space
L. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger · 2019
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Local deep implicit functions for 3D shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas A. Funkhouser · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 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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Generative 3d part assembly via dynamic graph learning
Guanqi Zhan, Qingnan Fan, Kaichun Mo, Lin Shao, Baoquan Chen, Leonidas J Guibas, Hao Dong, et al · 2020
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CodeNeRF: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 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, Gretchen Krueger, and Ilya Sutskever · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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In-place scene labelling and understanding with implicit scene representation
Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, and Andrew J. Davison · 2021
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SPAGHETTI: editing implicit shapes through part aware generation
Hertz Amir, Perel Or, Giryes Raja, Sorkine-Hornung Olga, and Cohen-Or Daniel · 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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Neural template: Topology-aware reconstruction and disentangled generation of 3d meshes
Ka-Hei Hui, Ruihui Li, Jingyu Hu, and Chi-Wing Fu · 2022
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Perceiver IO: A general architecture for structured inputs & outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, and João Carreira · 2022
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Decomposing NeRF for editing via feature field distillation
Sosuke Kobayashi, Eiichi Matsumoto, and Vincent Sitzmann · 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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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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Neural Feature Fusion Fields: 3D distillation of self-supervised 2D image representation
Vadim Tschernezki, Iro Laina, Diane Larlus, and Andrea Vedaldi · 2022
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Contrastive Lift: 3D object instance segmentation by slow-fast contrastive fusion
Yash Sanjay Bhalgat, Iro Laina, Joao F. Henriques, Andrea Vedaldi, and Andrew Zisserman · 2023
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Neural part priors: Learning to optimize part-based object completion in rgb-d scans
Aleksei Bokhovkin and Angela Dai · 2023
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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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Text-to-3D using Gaussian splatting
Zilong Chen, Feng Wang, and Huaping Liu · 2023
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Set-the-scene: Global-local training for generating controllable nerf scenes
Dana Cohen-Bar, Elad Richardson, Gal Metzer, Raja Giryes, and Daniel Cohen-Or · 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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3DGen: Triplane latent diffusion for textured mesh generation
Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, and Barlas Oguz · 2023
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Dreamtime: An improved optimization strategy for text-to-3D content creation
Yukun Huang, Jianan Wang, Yukai Shi, Xianbiao Qi, Zheng-Jun Zha, and Lei Zhang · 2023
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Shap-E: Generating conditional 3D implicit functions
Heewoo Jun and Alex Nichol · 2023
Cited alongside, same era.
3D Gaussian Splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
Cited alongside, same era.
LERF: language embedded radiance fields
Justin Kerr, Chung Min Kim, Ken Goldberg, Angjoo Kanazawa, and Matthew Tancik · 2023
Cited alongside, same era.
Segment anything
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.
Focaldreamer: Text-driven 3d editing via focal-fusion assembly, 2023
Yuhan Li, Yishun Dou, Yue Shi, Yu Lei, Xuanhong Chen, Yi Zhang, Peng Zhou, and Bingbing Ni · 2023
N2F2: Hierarchical scene understanding with nested neural feature fields
Yash Sanjay Bhalgat, Iro Laina, Joao F. Henriques, Andrew Zisserman, and Andrea Vedaldi · 2024
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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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Catvton: Concatenation is all you need for virtual try-on with diffusion models
Zheng Chong, Xiao Dong, Haoxiang Li, Shiyue Zhang, Wenqing Zhang, Xujie Zhang, Hanqing Zhao, and Xiaodan Liang · 2024
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CSM text-to-3D cube 2.0, 2024
CSM · 2024
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Rodin text-to-3D gen-1 (0525) v0.5, 2024
Deemos · 2024
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Disentangled 3d scene generation with layout learning, 2024
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Cited alongside, same era.
Composable part-based manipulation
Weiyu Liu, Jiayuan Mao, Joy Hsu, Tucker Hermans, Animesh Garg, and Jiajun Wu · 2023
Cited alongside, same era.
Wonder3D: Single image to 3D using cross-domain diffusion
Xiaoxiao Long, Yuanchen Guo, Cheng Lin, Yuan Liu, Zhiyang Dou, Lingjie Liu, Yuexin Ma, Song-Hai Zhang, Marc Habermann, Christian Theobalt, and Wenping Wang · 2023
Cited alongside, same era.
Scalable 3d captioning with pretrained models
Tiange Luo, Chris Rockwell, Honglak Lee, and Justin Johnson · 2023
Cited alongside, same era.
Grounding language with visual affordances over unstructured data
Oier Mees, Jessica Borja-Diaz, and Wolfram Burgard · 2023
Cited alongside, same era.
Differentiable blocks world: Qualitative 3d decomposition by rendering primitives
Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei Efros, and Mathieu Aubry · 2023
Cited alongside, same era.
DiffFacto: controllable part-based 3D point cloud generation with cross diffusion
George Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu, Ke Li, and Leonidas Guibas · 2023
Cited alongside, same era.
Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A. Efros, and Aleksander Holynski · 2024
Closest in time.
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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Flex3d: Feed-forward 3d generation with flexible reconstruction model and input view curation
Junlin Han, Jianyuan Wang, Andrea Vedaldi, Philip Torr, and Filippos Kokkinos · 2024
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ViewDiff: 3D-consistent image generation with text-to-image models
Lukas Höllein, Aljaz Bozic, Norman Müller, David Novotný, 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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Garfield: Group anything with radiance fields
Chung Min Kim, Mingxuan Wu, Justin Kerr, Ken Goldberg, Matthew Tancik, and Angjoo Kanazawa · 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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Common diffusion noise schedules and sample steps are flawed
Shanchuan Lin, Bingchen Liu, Jiashi Li, and Xiao Yang · 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
Closest in time.
Genie text-to-3D v1.0, 2024
LumaAI · 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
Closest in time.
Meshy text-to-3D v3.0, 2024
Meshy · 2024
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LangSplat: 3D language Gaussian splatting
Minghan Qin, Wanhua Li, Jiawei Zhou, Haoqian Wang, and Hanspeter Pfister · 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
Closest in time.
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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Meta 3D Asset Gen: Text-to-mesh generation with high-quality geometry, texture, and PBR materials
Yawar Siddiqui, Filippos Kokkinos, Tom Monnier, Mahendra Kariya, Yanir Kleiman, Emilien Garreau, Oran Gafni, Natalia Neverova, Andrea Vedaldi, Roman Shapovalov, and David Novotny · 2024
Closest in time.
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
Closest in time.
Tripo3D text-to-3D, 2024
TripoAI · 2024
Closest in time.
ImageDream: Image-prompt multi-view diffusion for 3D generation
Peng Wang and Yichun Shi · 2024
Closest in time.
Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning
Haiyang Ying, Yixuan Yin, Jinzhi Zhang, Fan Wang, Tao Yu, Ruqi Huang, and Lu Fang · 2024
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Uni3D: Exploring unified 3D representation at scale
Junsheng Zhou, Jinsheng Wang, Baorui Ma, Yu-Shen Liu, Tiejun Huang, and Xinlong Wang · 2024
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Dreamdissector: Learning disentangled text-to-3d generation from 2d diffusion priors
Yan Zizheng, Zhou Jiapeng, Meng Fanpeng, Wu Yushuang, Qiu Lingteng, Ye Zisheng, Cui Shuguang, Chen Guanying, and Han Xiaoguang · 2024
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Vfusion3d: Learning scalable 3d generative models from video diffusion models
Junlin Han, Filippos Kokkinos, and Philip Torr · 2025
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