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Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation.
The shannon sampling theorem—its various extensions and applications: A tutorial review
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What can be seen in three dimensions with an uncalibrated stereo rig?
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Ewa volume splatting
Matthias Zwicker, Hanspeter Pfister, Jeroen Van Baar, and Markus Gross · 2001
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A practical procedure to estimate the shape parameter in the generalized gaussian distribution
J Armando Dominguez-Molina, Graciela González-Farías, Ramón M Rodríguez-Dagnino, and ITESM Campus Monterrey · 2003
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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Building rome in a day
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Point-based graphics
Markus Gross and Hanspeter Pfister · 2011
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Opendr: An approximate differentiable renderer
Matthew M Loper and Michael J Black · 2014
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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Tanks and temples: Benchmarking large-scale scene reconstruction
Arno Knapitsch, Jaesik Park, Qian-Yi Zhou, and Vladlen Koltun · 2017
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Deep blending for free-viewpoint image-based rendering
Peter Hedman, Julien Philip, True Price, Jan-Michael Frahm, George Drettakis, and Gabriel Brostow · 2018
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Deepmvs: Learning multi-view stereopsis
Po-Han Huang, Kevin Matzen, Johannes Kopf, Narendra Ahuja, and Jia-Bin Huang · 2018
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Neural 3d mesh renderer
Hiroharu Kato, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Paparazzi: surface editing by way of multi-view image processing
Hsueh-Ti Derek Liu, Michael Tao, and Alec Jacobson · 2018
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao Yao, Zixin Luo, Shiwei Li, Tian Fang, and Long Quan · 2018
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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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Soft rasterizer: A differentiable renderer for image-based 3d reasoning
Shichen Liu, Tianye Li, Weikai Chen, and Hao Li · 2019
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Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
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PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Pix2vex: Image-to-geometry reconstruction using a smooth differentiable renderer
Felix Petersen, Amit H Bermano, Oliver Deussen, and Daniel Cohen-Or · 2019
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Recurrent mvsnet for high-resolution multi-view stereo depth inference
Yao Yao, Zixin Luo, Shiwei Li, Tianwei Shen, Tian Fang, and Long Quan · 2019
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Differentiable surface splatting for point-based geometry processing
Wang Yifan, Felice Serena, Shihao Wu, Cengiz Öztireli, and Olga Sorkine-Hornung · 2019
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Neural point-based graphics
Kara-Ali Aliev, Artem Sevastopolsky, Maria Kolos, Dmitry Ulyanov, and Victor Lempitsky · 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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Synsin: End-to-end view synthesis from a single image
Olivia Wiles, Georgia Gkioxari, Richard Szeliski, and Justin Johnson · 2020
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Multiview neural surface reconstruction by disentangling geometry and appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Basri Ronen, and Yaron Lipman · 2020
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Fast-mvsnet: Sparse-to-dense multi-view stereo with learned propagation and gauss-newton refinement
Zehao Yu and Shenghua Gao · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
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Barf: Bundle-adjusting neural radiance fields
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey · 2021
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Nerf in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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D-nerf: Neural radiance fields for dynamic scenes
Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
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Learning transferable visual models from natural language supervision
Stable-dreamfusion: Text-to-3d with stable-diffusion, 2022
Jiaxiang Tang · 2022
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Ref-nerf: Structured view-dependent appearance for neural radiance fields
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T Barron, and Pratul P Srinivasan · 2022
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Hf-neus: Improved surface reconstruction using high-frequency details
Yiqun Wang, Ivan Skorokhodov, and Peter Wonka · 2022
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Point-nerf: Point-based neural radiance fields
Qiangeng Xu, Zexiang Xu, Julien Philip, Sai Bi, Zhixin Shu, Kalyan Sunkavalli, and Ulrich Neumann · 2022
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Monosdf: Exploring monocular geometric cues for neural implicit surface reconstruction
Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, and Andreas Geiger · 2022
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Differentiable point-based radiance fields for efficient view synthesis
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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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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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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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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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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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Plenoxels: Radiance fields without neural networks
Alex Yu, Sara Fridovich-Keil, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 2021
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PlenOctrees for real-time rendering of neural radiance fields
Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, and Angjoo Kanazawa · 2021
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Qiang Zhang, Seung-Hwan Baek, Szymon Rusinkiewicz, and Felix Heide · 2022
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Zip-nerf: Anti-aliased grid-based neural radiance fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman · 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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Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
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Text-to-3d using gaussian splatting
Zilong Chen, Feng Wang, and Huaping Liu · 2023
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Sdfusion: Multimodal 3d shape completion, reconstruction, and generation
Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov, Alexander G Schwing, and Liang-Yan Gui · 2023
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Objaverse-xl: A universe of 10m+ 3d objects
Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, et al · 2023
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Learning to render novel views from wide-baseline stereo pairs
Yilun Du, Cameron Smith, Ayush Tewari, and Vincent Sitzmann · 2023
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Text2room: Extracting textured 3d meshes from 2d text-to-image models
Lukas Höllein, Ang Cao, Andrew Owens, Justin Johnson, and Matthias Nießner · 2023
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Farm3d: Learning articulated 3d animals by distilling 2d diffusion
Tomas Jakab, Ruining Li, Shangzhe Wu, Christian Rupprecht, and Andrea Vedaldi · 2023
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3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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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 · 2023
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What you can reconstruct from a shadow
Ruoshi Liu, Sachit Menon, Chengzhi Mao, Dennis Park, Simon Stent, and Carl Vondrick · 2023
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Humans as light bulbs: 3d human reconstruction from thermal reflection
Ruoshi Liu and Carl Vondrick · 2023
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Zero-1-to-3: Zero-shot one image to 3d object
Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, and Carl Vondrick · 2023
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Sked: Sketch-guided text-based 3d editing
Aryan Mikaeili, Or Perel, Daniel Cohen-Or, and Ali Mahdavi-Amiri · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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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, and Bernard Ghanem · 2023
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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
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Texture: Text-guided texturing of 3d shapes
Elad Richardson, Gal Metzer, Yuval Alaluf, Raja Giryes, and Daniel Cohen-Or · 2023
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Ditto-nerf: Diffusion-based iterative text to omni-directional 3d model
Hoigi Seo, Hayeon Kim, Gwanghyun Kim, and Se Young Chun · 2023
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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
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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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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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