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Impressive progress in generative models and implicit representations gave rise to methods that can generate 3D shapes of high quality.
Ray tracing volume densities
James T. Kajiya and Brian Von Herzen · 1984
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Marching cubes: A high resolution 3d surface construction algorithm
William E. Lorensen and Harvey E. Cline · 1987
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Mean value coordinates
Michael S Floater · 2003
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Harmonic coordinates for character articulation
Pushkar Joshi, Mark Meyer, Tony DeRose, Brian Green, and Tom Sanocki · 2007
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As-rigid-as-possible surface modeling
Olga Sorkine and Marc Alexa · 2007
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Green coordinates
Yaron Lipman, David Levin, and Daniel Cohen-Or · 2008
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Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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Shapenet: An information-rich 3d model repository
Angel X. Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Linear subspace design for real-time shape deformation
Yu Wang, Alec Jacobson, Jernej Barbic, and Ladislav Kavan · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Enet: A deep neural network architecture for real-time semantic segmentation
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, and Eugenio Culurciello · 2016
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State of the art in artistic editing of appearance, lighting and material
Thorsten-Walther Schmidt, Fabio Pellacini, Derek Nowrouzezahrai, Wojciech Jarosz, and Carsten Dachsbacher · 2016
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Modulating early visual processing by language
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, and Aaron C. Courville · 2017
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3d shape induction from 2d views of multiple objects
Matheus Gadelha, Subhransu Maji, and Rui Wang · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
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GRASS: generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao (Richard) Zhang, and Leonidas J. Guibas · 2017
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Learning shape abstractions by assembling volumetric primitives
Shubham Tulsiani, Hao Su, Leonidas J. Guibas, Alexei A. Efros, and Jitendra Malik · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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3d-prnn: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
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Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J. Guibas · 2018
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Optimizing the latent space of generative networks
Piotr Bojanowski, Armand Joulin, David Lopez-Paz, and Arthur Szlam · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Min-Je Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
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Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Im2struct: Recovering 3d shape structure from a single RGB image
Chengjie Niu, Jun Li, and Kai Xu · 2018
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Controlling neural level sets
Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, and Yaron Lipman · 2019
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Learning elementary structures for 3d shape generation and matching
Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2019
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SDM-NET: deep generative network for structured deformable mesh
Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, 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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Learning single-image 3d reconstruction by generative modelling of shape, pose and shading
Paul Henderson and Vittorio Ferrari · 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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Supervised fitting of geometric primitives to 3d point clouds
Lingxiao Li, Minhyuk Sung, Anastasia Dubrovina, Li Yi, and Leonidas Guibas · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Implicit surface representations as layers in neural networks
Mateusz Michalkiewicz, Jhony K Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
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Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas Guibas · 2019
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Hologan: Unsupervised learning of 3d representations from natural images
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, and Yong-Liang Yang · 2019
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Hologan: Unsupervised learning of 3d representations from natural images
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, and Yong-Liang Yang · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard A. Newcombe, and Steven Lovegrove · 2019
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Superquadrics revisited: Learning 3d shape parsing beyond cuboids
Despoina Paschalidou, Ali Osman Ulusoy, and Andreas Geiger · 2019
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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
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Pytorch image models
Ross Wightman · 2019
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DISN: deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomír Mech, and Ulrich Neumann · 2019
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simple-3dviz
Katharopoulos Angelos and Despoina Paschalidou · 2020
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SAL: sign agnostic learning of shapes from raw data
Matan Atzmon and Yaron Lipman · 2020
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Neural reflectance fields for appearance acquisition
Sai Bi, Zexiang Xu, Pratul P. Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Milos Hasan, Yannick Hold-Geoffroy, David J. Kriegman, and Ravi Ramamoorthi · 2020
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Implicit functions in feature space for 3d shape reconstruction and completion
Julian Chibane, Thiemo Alldieck, and Gerard Pons-Moll · 2020
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Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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Cvxnets: Learnable convex decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, and Andrea Tagliasacchi · 2020
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Learning deformable tetrahedral meshes for 3d reconstruction
Jun Gao, Wenzheng Chen, Tommy Xiang, Alec Jacobson, Morgan McGuire, and Sanja Fidler · 2020
Cited alongside, same era.
Local deep implicit functions for 3d shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas A. Funkhouser · 2020
Cited alongside, same era.
Local deep implicit functions for 3d shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas A. Funkhouser · 2020
Codenerf: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 2021
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Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
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SP-GAN: sphere-guided 3d shape generation and manipulation
Ruihui Li, Xianzhi Li, Ka-Hei Hui, and Chi-Wing Fu · 2021
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Autoint: Automatic integration for fast neural volume rendering
David B. Lindell, Julien N. P. Martel, and Gordon Wetzstein · 2021
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Editing conditional radiance fields
Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, and Bryan Russell · 2021
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Nerf in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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Cited alongside, same era.
Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Cited alongside, same era.
Dualsdf: Semantic shape manipulation using a two-level representation
Zekun Hao, Hadar Averbuch-Elor, Noah Snavely, and Serge J. Belongie · 2020
Cited alongside, same era.
Unsupervised object-centric video generation and decomposition in 3d
Paul Henderson and Christoph H. Lampert · 2020
Cited alongside, same era.
Local implicit grid representations for 3d scenes
Chiyu Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, and Thomas Funkhouser · 2020
Cited alongside, same era.
Analyzing and improving the image quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Neural star domain as primitive representation
Yuki Kawana, Yusuke Mukuta, and Tatsuya Harada · 2020
Cited alongside, same era.
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Gnerf: Gan-based neural radiance field without posed camera
Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, and Jingyi Yu · 2021
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CAMPARI: camera-aware decomposed generative neural radiance fields
Michael Niemeyer and Andreas Geiger · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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UNISURF: unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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Neural parts: Learning expressive 3d shape abstractions with invertible neural networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger, and Sanja Fidler · 2021
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Derf: Decomposed radiance fields
Daniel Rebain, Wei Jiang, Soroosh Yazdani, Ke Li, Kwang Moo Yi, and Andrea Tagliasacchi · 2021
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Kilonerf: Speeding up neural radiance fields with thousands of tiny mlps
Christian Reiser, Songyou Peng, Yiyi Liao, and Andreas Geiger · 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 Novotný · 2021
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Nerv: Neural reflectance and visibility fields for relighting and view synthesis
Pratul P. Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T. Barron · 2021
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Learned initializations for optimizing coordinate-based neural representations
Matthew Tancik, Ben Mildenhall, Terrance Wang, Divi Schmidt, Pratul P. Srinivasan, Jonathan T. Barron, and Ren Ng · 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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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 A. Funkhouser · 2021
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Learning object-compositional neural radiance field for editable scene rendering
Bangbang Yang, Yinda Zhang, Yinghao Xu, Yijin Li, Han Zhou, Hujun Bao, Guofeng Zhang, and Zhaopeng Cui · 2021
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Discovering 3d parts from image collections
Chun-Han Yao, Wei-Chih Hung, Varun Jampani, and Ming-Hsuan Yang · 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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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Image gans meet differentiable rendering for inverse graphics and interpretable 3d neural rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, and Sanja Fidler · 2021
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Cips-3d: A 3d-aware generator of gans based on conditionally-independent pixel synthesis
Peng Zhou, Lingxi Xie, Bingbing Ni, and Qi Tian · 2021
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Efficient geometry-aware 3d generative adversarial networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J. Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, and Gordon Wetzstein · 2022
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Cross-modal 3d shape generation and manipulation
Zezhou Cheng, Menglei Chai, Jian Ren, Hsin-Ying Lee, Kyle Olszewski, Zeng Huang, Subhransu Maji, and Sergey Tulyakov · 2022
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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
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Stylenerf: A style-based 3d aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2022
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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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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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Conerf: Controllable neural radiance fields
Kacper Kania, Kwang Moo Yi, Marek Kowalski, Tomasz Trzciński, and Andrea Tagliasacchi · 2022
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Control-nerf: Editable feature volumes for scene rendering and manipulation
Verica Lazova, Vladimir Guzov, Kyle Olszewski, Sergey Tulyakov, and Gerard Pons-Moll · 2022
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Neuform: Adaptive overfitting for neural shape editing
Connor Z. Lin, Niloy J. Mitra, Gordon Wetzstein, Leonidas J. Guibas, and Paul Guerrero · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Watch it move: Unsupervised discovery of 3d joints for re-posing of articulated objects
Atsuhiro Noguchi, Umar Iqbal, Jonathan Tremblay, Tatsuya Harada, and Orazio Gallo · 2022
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ANISE: assembly-based neural implicit surface reconstruction
Dmitry Petrov, Matheus Gadelha, Radomír Mech, and Evangelos Kalogerakis · 2022
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Ide-3d: Interactive disentangled editing for high-resolution 3d-aware portrait synthesis
Jingxiang Sun, Xuan Wang, Yichun Shi, Lizhen Wang, Jue Wang, and Yebin Liu · 2022
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Fenerf: Face editing in neural radiance fields
Jingxiang Sun, Xuan Wang, Yong Zhang, Xiaoyu Li, Qi Zhang, Yebin Liu, and Jue Wang · 2022
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Fenerf: Face editing in neural radiance fields
Jingxiang Sun, Xuan Wang, Yong Zhang, Xiaoyu Li, Qi Zhang, Yebin Liu, and Jue Wang · 2022
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Advances in neural rendering
Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul P. Srinivasan, Edgar Tretschk, Yifan Wang, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, Tomas Simon, Christian Theobalt, Matthias Nießner, Jonathan T. Barron, Gordon Wetzstein, Michael Zollhöfer, and Vladislav Golyanik · 2022
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Neural fields in visual computing and beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2022
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GIRAFFE HD: A high-resolution 3d-aware generative model
Yang Xue, Yuheng Li, Krishna Kumar Singh, and Yong Jae Lee · 2022
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Neumesh: Learning disentangled neural mesh-based implicit field for geometry and texture editing
Bangbang Yang, Chong Bao, Junyi Zeng, Hujun Bao, Yinda Zhang, Zhaopeng Cui, and Guofeng Zhang · 2022
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LASSIE: learning articulated shapes from sparse image ensemble via 3d part discovery
Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, and Varun Jampani · 2022
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Nerf-editing: Geometry editing of neural radiance fields
Yu-Jie Yuan, Yang-Tian Sun, Yu-Kun Lai, Yuewen Ma, Rongfei Jia, and Lin Gao · 2022
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