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Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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 shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
Earlier work this paper cites.
Large-scale data for multiple-view stereopsis
Henrik Aanæs, Rasmus Ramsbøl Jensen, George Vogiatzis, Engin Tola, and Anders Bjorholm Dahl · 2016
Earlier work this paper cites.
Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
Earlier work this paper cites.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
Earlier work this paper cites.
3d shape induction from 2d views of multiple objects
Matheus Gadelha, Subhransu Maji, and Rui Wang · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Improved adversarial systems for 3d object generation and reconstruction
Edward J Smith and David Meger · 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.
Blender - a 3d modelling and rendering package
Blender Online Community · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Open3D: A modern library for 3D data processing
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2018
Earlier work this paper cites.
Controlling neural level sets
Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, and Yaron Lipman · 2019
Earlier work this paper cites.
Learning to predict 3d objects with an interpolation-based differentiable renderer
Wenzheng Chen, Huan Ling, Jun Gao, Edward Smith, Jaakko Lehtinen, Alec Jacobson, and Sanja Fidler · 2019
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
Earlier work this paper cites.
Escaping plato’s cave: 3d shape from adversarial rendering
Philipp Henzler, Niloy J Mitra, and Tobias Ritschel · 2019
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Earlier work this paper cites.
Relation-shape convolutional neural network for point cloud analysis
Yongcheng Liu, Bin Fan, Shiming Xiang, and Chunhong Pan · 2019
Earlier work this paper cites.
Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 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
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.
Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy J. Mitra, and Leonidas J. Guibas · 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.
Semantic image synthesis with spatially-adaptive normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, and Jun-Yan Zhu · 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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Objects365: A large-scale, high-quality dataset for object detection
Shuai Shao, Zeming Li, Tianyuan Zhang, Chao Peng, Gang Yu, Xiangyu Zhang, Jing Li, and Jian Sun · 2019
Earlier work this paper cites.
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
Earlier work this paper cites.
Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data
Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua, Thanh Nguyen, and Sai-Kit Yeung · 2019
Earlier work this paper cites.
Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
Earlier work this paper cites.
Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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Pointmixup: Augmentation for point clouds
Yunlu Chen, Vincent Tao Hu, Efstratios Gavves, Thomas Mensink, Pascal Mettes, Pengwan Yang, and Cees GM Snoek · 2020
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F, b, alpha matting
Marco Forte and François Pitié · 2020
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Sdfdiff: Differentiable rendering of signed distance fields for 3d shape optimization
Yue Jiang, Dantong Ji, Zhizhong Han, and Matthias Zwicker · 2020
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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The open images dataset v4
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, et al · 2020
Using shape to categorize: Low-shot learning with an explicit shape bias
Stefan Stojanov, Anh Thai, and James M Rehg · 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 Funkhouser · 2021
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Walk in the cloud: Learning curves for point clouds shape analysis
Tiange Xiang, Chaoyi Zhang, Yang Song, Jianhui Yu, and Weidong Cai · 2021
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Paconv: Position adaptive convolution with dynamic kernel assembling on point clouds
Mutian Xu, Runyu Ding, Hengshuang Zhao, and Xiaojuan Qi · 2021
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Dist: Rendering deep implicit signed distance function with differentiable sphere tracing
Shaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, and Zhaopeng Cui · 2020
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Inverse graphics gan: Learning to generate 3d shapes from unstructured 2d data
Sebastian Lunz, Yingzhen Li, Andrew Fitzgibbon, and Nate Kushman · 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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Polygen: An autoregressive generative model of 3d meshes
Charlie Nash, Yaroslav Ganin, SM Ali Eslami, and Peter Battaglia · 2020
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Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
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U2-net: Going deeper with nested u-structure for salient object detection
Xuebin Qin, Zichen Zhang, Chenyang Huang, Masood Dehghan, Osmar R Zaiane, and Martin Jagersand · 2020
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Learning geometry-disentangled representation for complementary understanding of 3d object point cloud
Mutian Xu, Junhao Zhang, Zhipeng Zhou, Mingye Xu, Xiaojuan Qi, and Yu Qiao · 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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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Learning signed distance field for multi-view surface reconstruction
Jingyang Zhang, Yao Yao, and Long Quan · 2021
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3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 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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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman · 2022
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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, et al · 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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Abo: Dataset and benchmarks for real-world 3d object understanding
Jasmine Collins, Shubham Goel, Kenan Deng, Achleshwar Luthra, Leon Xu, Erhan Gundogdu, Xi Zhang, Tomas F Yago Vicente, Thomas Dideriksen, Himanshu Arora, et al · 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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Plenoxels: Radiance fields without neural networks
Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 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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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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Multimodal conditional image synthesis with product-of-experts gans
Xun Huang, Arun Mallya, Ting-Chun Wang, and Ming-Yu Liu · 2022
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Octree transformer: Autoregressive 3d shape generation on hierarchically structured sequences
Moritz Ibing, Gregor Kobsik, and Leif Kobbelt · 2022
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Akb-48: A real-world articulated object knowledge base
Liu Liu, Wenqiang Xu, Haoyuan Fu, Sucheng Qian, Qiaojun Yu, Yang Han, and Cewu Lu · 2022
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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
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Sparseneus: Fast generalizable neural surface reconstruction from sparse views
Xiaoxiao Long, Cheng Lin, Peng Wang, Taku Komura, and Wenping Wang · 2022
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Nerf in the dark: High dynamic range view synthesis from noisy raw images
Ben Mildenhall, Peter Hedman, Ricardo Martin-Brualla, Pratul P Srinivasan, and Jonathan T Barron · 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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Stylesdf: High-resolution 3d-consistent image and geometry generation
Roy Or-El, Xuan Luo, Mengyi Shan, Eli Shechtman, Jeong Joon Park, and Ira Kemelmacher-Shlizerman · 2022
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Benchmarking and analyzing point cloud classification under corruptions
Jiawei Ren, Liang Pan, and Ziwei Liu · 2022
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Voxgraf: Fast 3d-aware image synthesis with sparse voxel grids
Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, and Andreas Geiger · 2022
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Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction
Cheng Sun, Min Sun, and Hwann-Tzong Chen · 2022
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Fast Gradient Descent for Surface Capture Via Differentiable Rendering
Briac Toussaint, Maxime Genisson, and Jean-Sébastien Franco · 2022
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Is attention all nerf needs?
Mukund Varma, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang, and Madras · 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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Voxurf: Voxel-based efficient and accurate neural surface reconstruction
Tong Wu, Jiaqi Wang, Xingang Pan, Xudong Xu, Christian Theobalt, Ziwei Liu, and Dahua Lin · 2022
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3d-aware image synthesis via learning structural and textural representations
Yinghao Xu, Sida Peng, Ceyuan Yang, Yujun Shen, and Bolei Zhou · 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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