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Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts.
3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
Christopher B Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese · 2016
Earlier work this paper cites.
A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Marrnet: 3d shape reconstruction via 2.5 d sketches
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, and Josh Tenenbaum · 2017
Earlier work this paper cites.
Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
Earlier work this paper cites.
A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
Earlier work this paper cites.
Learning category-specific mesh reconstruction from image collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A Efros, and Jitendra Malik · 2018
Earlier work this paper cites.
Pixel2mesh: Generating 3d mesh models from single rgb images
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
Earlier work this paper cites.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Earlier work this paper cites.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Earlier work this paper cites.
Pix2vox: Context-aware 3d reconstruction from single and multi-view images
Haozhe Xie, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, and Shengping Zhang · 2019
Earlier work this paper cites.
Disn: Deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, and Ulrich Neumann · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Polygen: An autoregressive generative model of 3d meshes
Charlie Nash, Yaroslav Ganin, SM Ali Eslami, and Peter Battaglia · 2020
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Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, and Hao Su · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Earlier work this paper cites.
Deepmetahandles: Learning deformation meta-handles of 3d meshes with biharmonic coordinates
Minghua Liu, Minhyuk Sung, Radomir Mech, and Hao Su · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, 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.
Grf: Learning a general radiance field for 3d representation and rendering
Alex Trevithick and Bo Yang · 2021
Earlier work this paper cites.
Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P Srinivasan, Howard Zhou, Jonathan T Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
Earlier work this paper cites.
Tensorf: Tensorial radiance fields
Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
Get3d: A generative model of high quality 3d textured shapes learned from images
Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler · 2022
Cited alongside, same era.
Avatarclip: Zero-shot text-driven generation and animation of 3d avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, and Ziwei Liu · 2022
Cited alongside, same era.
Zero-shot text-guided object generation with dream fields
Ajay Jain, Ben Mildenhall, Jonathan T Barron, Pieter Abbeel, and Ben Poole · 2022
Cited alongside, same era.
Geonerf: Generalizing nerf with geometry priors
Mohammad Mahdi Johari, Yann Lepoittevin, and François Fleuret · 2022
Cited alongside, same era.
Viewformer: Nerf-free neural rendering from few images using transformers
Jonáš Kulhánek, Erik Derner, Torsten Sattler, and Robert Babuška · 2022
Cited alongside, same era.
3dgen: Triplane latent diffusion for textured mesh generation
Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, and Barlas Oğuz · 2023
Closest in time.
Shap-e: Generating conditional 3d implicit functions
Heewoo Jun and Alex Nichol · 2023
Closest in time.
Holodiffusion: Training a 3d diffusion model using 2d images
Animesh Karnewar, Andrea Vedaldi, David Novotny, and Niloy J Mitra · 2023
Closest in time.
Diffusion-sdf: Text-to-shape via voxelized diffusion
Muheng Li, Yueqi Duan, Jie Zhou, and Jiwen Lu · 2023
Closest in time.
Wonder3d: Single image to 3d using cross-domain diffusion, 2023
Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin, Yuan Liu, Zhiyang Dou, Lingjie Liu, Yuexin Ma, Song-Hai Zhang, Marc Habermann, Christian Theobalt, and Wenping Wang · 2023
Closest in time.
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Han-Hung Lee and Angel X Chang · 2022
Cited alongside, same era.
Neural rays for occlusion-aware image-based rendering
Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, and Wenping Wang · 2022
Cited alongside, same era.
Sparseneus: Fast generalizable neural surface reconstruction from sparse views
Xiaoxiao Long, Cheng Lin, Peng Wang, Taku Komura, and Wenping Wang · 2022
Cited alongside, same era.
Text2mesh: Text-driven neural stylization for meshes
Oscar Michel, Roi Bar-On, Richard Liu, Sagie Benaim, and Rana Hanocka · 2022
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.
Point-e: A system for generating 3d point clouds from complex prompts
Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen · 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.
Latent-nerf for shape-guided generation of 3d shapes and textures
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2023
Closest in time.
Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, et al · 2023
Closest in time.
Dreambooth3d: Subject-driven text-to-3d generation
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan Barron, et al · 2023
Closest in time.
Volrecon: Volume rendering of signed ray distance functions for generalizable multi-view reconstruction
Yufan Ren, Tong Zhang, Marc Pollefeys, Sabine Süsstrunk, and Fangjinhua Wang · 2023
Closest in time.
Texture: Text-guided texturing of 3d shapes
Elad Richardson, Gal Metzer, Yuval Alaluf, Raja Giryes, and Daniel Cohen-Or · 2023
Closest in time.
Let 2d diffusion model know 3d-consistency for robust text-to-3d generation
Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Jaehoon Ko, Hyeonsu Kim, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, and Seungryong Kim · 2023
Closest in time.
Mvdream: Multi-view diffusion for 3d generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2023
Closest in time.
Diffusion with forward models: Solving stochastic inverse problems without direct supervision
Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Joshua B Tenenbaum, Frédo Durand, William T Freeman, and Vincent Sitzmann · 2023
Closest in time.
Consistent123: Improve consistency for one image to 3d object synthesis
Haohan Weng, Tianyu Yang, Jianan Wang, Yu Li, Tong Zhang, CL Chen, and Lei Zhang · 2023
Closest in time.
Multiview compressive coding for 3d reconstruction
Chao-Yuan Wu, Justin Johnson, Jitendra Malik, Christoph Feichtenhofer, and Georgia Gkioxari · 2023
Closest in time.
Contranerf: Generalizable neural radiance fields for synthetic-to-real novel view synthesis via contrastive learning
Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, and Liwei Wang · 2023
Closest in time.
Consistent-1-to-3: Consistent image to 3d view synthesis via geometry-aware diffusion models
Jianglong Ye, Peng Wang, Kejie Li, Yichun Shi, and Heng Wang · 2023
Closest in time.
3dshape2vecset: A 3d shape representation for neural fields and generative diffusion models
Biao Zhang, Jiapeng Tang, Matthias Niessner, and Peter Wonka · 2023
Closest in time.
Reference-only control
Lyumin Zhang · 2023
Closest in time.
Zibo Zhao, Wen Liu, Xin Chen, Xianfang Zeng, Rui Wang, Pei Cheng, Bin Fu, Tao Chen, Gang Yu, and Shenghua Gao · 2023
Closest in time.
Locally attentional sdf diffusion for controllable 3d shape generation
Xin-Yang Zheng, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, and Heung-Yeung Shum · 2023
Closest in time.
Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhizhuo Zhou and Shubham Tulsiani · 2023
Closest in time.