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Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world.
Marching cubes: A high resolution 3d surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
Earlier work this paper cites.
Automatic class-specific 3d reconstruction from a single image
Han-Pang Chiu, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2009
Earlier work this paper cites.
Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
Earlier work this paper cites.
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.
Learning a predictable and generative vector representation for objects
Rohit Girdhar, David F Fouhey, Mikel Rodriguez, and Abhinav Gupta · 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.
3d menagerie: Modeling the 3d shape and pose of animals
Silvia Zuffi, Angjoo Kanazawa, David W Jacobs, and Michael J Black · 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 collectionsgirdhar2016learning
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.
Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
Earlier work this paper cites.
Lions and tigers and bears: Capturing non-rigid, 3d, articulated shape from images
Silvia Zuffi, Angjoo Kanazawa, and Michael J Black · 2018
Earlier work this paper cites.
Self-supervised 3d shape and viewpoint estimation from single images for robotics
Oier Mees, Maxim Tatarchenko, Thomas Brox, and Wolfram Burgard · 2019
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
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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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Expressive body capture: 3d hands, face, and body from a single image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed AA Osman, Dimitrios Tzionas, and Michael J Black · 2019
Earlier work this paper cites.
Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization
Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, and Hao Li · 2019
Earlier work this paper cites.
Pixel2mesh++: Multi-view 3d mesh generation via deformation
Chao Wen, Yinda Zhang, Zhuwen Li, and Yanwei Fu · 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
Earlier work this paper cites.
Polygen: An autoregressive generative model of 3d meshes
Charlie Nash, Yaroslav Ganin, SM Ali Eslami, and Peter Battaglia · 2020
Earlier work this paper cites.
Pix2vox++: Multi-scale context-aware 3d object reconstruction from single and multiple images
Haozhe Xie, Hongxun Yao, Shengping Zhang, Shangchen Zhou, and Wenxiu Sun · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Unsupervised learning of 3d object categories from videos in the wild
Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, and David Novotny · 2021
Earlier work this paper cites.
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.
Codenerf: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 2021
Earlier work this paper cites.
Clipmatrix: Text-controlled creation of 3d textured meshes
Nikolay Jetchev · 2021
Earlier work this paper cites.
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 · 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
Earlier work this paper cites.
Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
Jeremy Reizenstein, Roman Shapovalov, Philipp Henzler, Luca Sbordone, Patrick Labatut, and David Novotny · 2021
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Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
Jeremy Reizenstein, Roman Shapovalov, Philipp Henzler, Luca Sbordone, Patrick Labatut, and David Novotny · 2021
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Loftr: Detector-free local feature matching with transformers
Jiaming Sun, Zehong Shen, Yuang Wang, Hujun Bao, and Xiaowei Zhou · 2021
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Grf: Learning a general radiance field for 3d representation and rendering
Alex Trevithick and Bo Yang · 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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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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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Yufan Ren, Fangjinhua Wang, Tong Zhang, Marc Pollefeys, and Sabine Süsstrunk · 2022
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High-resolution image synthesis with latent diffusion models
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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
Cited alongside, same era.
Legoformer: Transformers for block-by-block multi-view 3d reconstruction
Farid Yagubbayli, Yida Wang, Alessio Tonioni, and Federico Tombari · 2021
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Robotic grasping through combined image-based grasp proposal and 3d reconstruction
Daniel Yang, Tarik Tosun, Benjamin Eisner, Volkan Isler, and Daniel Lee · 2021
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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Clipface: Text-guided editing of textured 3d morphable models
Shivangi Aneja, Justus Thies, Angela Dai, and Matthias Nießner · 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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Sdfusion: Multimodal 3d shape completion, reconstruction, and generation
Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov, Alexander Schwing, and Liangyan Gui · 2022
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Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Clip-forge: Towards zero-shot text-to-shape generation
Aditya Sanghi, Hang Chu, Joseph G Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, and Kamal Rahimi Malekshan · 2022
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Is attention all that nerf needs?
Mukund Varma, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, and Zhangyang Wang · 2022
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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 · 2022
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Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Yi Wang, and Zhangyang Wang · 2022
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Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao · 2022
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Lion: Latent point diffusion models for 3d shape generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis · 2022
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Nerfusion: Fusing radiance fields for large-scale scene reconstruction
Xiaoshuai Zhang, Sai Bi, Kalyan Sunkavalli, Hao Su, and Zexiang Xu · 2022
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Text and image guided 3d avatar generation and manipulation
Zehranaz Canfes, M Furkan Atasoy, Alara Dirik, and Pinar Yanardag · 2023
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Text2tex: Text-driven texture synthesis via diffusion models
Dave Zhenyu Chen, Yawar Siddiqui, Hsin-Ying Lee, Sergey Tulyakov, and Matthias Nießner · 2023
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Blenderproc2: A procedural pipeline for photorealistic rendering
Maximilian Denninger, Dominik Winkelbauer, Martin Sundermeyer, Wout Boerdijk, Markus Knauer, Klaus H. Strobl, Matthias Humt, and Rudolph Triebel · 2023
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3dgen: Triplane latent diffusion for textured mesh generation
Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, and Barlas Oğuz · 2023
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Shap-e: Generating conditional 3d implicit functions
Heewoo Jun and Alex Nichol · 2023
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Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, and Carl Vondrick · 2023
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Iss++: Image as stepping stone for text-guided 3d shape generation
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Realfusion: 360 { \{ \ \backslash deg } \} reconstruction of any object from a single image
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p c 2 pc2 : Projection—conditioned point cloud diffusion for single-image 3d reconstruction
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Dreambooth3d: Subject-driven text-to-3d generation
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Texture: Text-guided texturing of 3d shapes
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Let 2d diffusion model know 3d-consistency for robust text-to-3d generation
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Taps3d: Text-guided 3d textured shape generation from pseudo supervision, 2023
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Multiview compressive coding for 3d reconstruction
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Adding conditional control to text-to-image diffusion models, 2023
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Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
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