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Low-level 3D representations, such as point clouds, meshes, NeRFs and 3D Gaussians, are commonly used for modeling 3D objects and scenes.
Machine perception of three-dimensional solids
Lawrence G. Roberts · 1963
Earlier work this paper cites.
Visual Perception by Computer
Thomas Binford · 1971
Earlier work this paper cites.
Superquadrics and Angle-Preserving Transformations
Alan H. Barr · 1981
Earlier work this paper cites.
Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
Martin A. Fischler and Robert C. Bolles · 1981
Earlier work this paper cites.
Compositing Digital Images
Thomas Porter and Tom Duff · 1984
Earlier work this paper cites.
Numerics of gram-schmidt orthogonalization
Åke Björck · 1994
Earlier work this paper cites.
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.
Structure-aware shape processing
Niloy Mitra, Michael Wand, Hao (Richard) Zhang, Daniel Cohen-Or, Vladimir Kim, and Qi-Xing Huang · 2013
Earlier work this paper cites.
Large Scale Multi-view Stereopsis Evaluation
Rasmus Jensen, Anders Dahl, George Vogiatzis, Engil Tola, and Henrik Aanaes · 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, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
Earlier work this paper cites.
Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
Earlier work this paper cites.
Grass: Generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, and Leonidas Guibas · 2017
Earlier work this paper cites.
Dbscan revisited, revisited: why and how you should (still) use dbscan
Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, and Xiaowei Xu · 2017
Earlier work this paper cites.
Learning Shape Abstractions by Assembling Volumetric Primitives
Shubham Tulsiani, Hao Su, Leonidas J. Guibas, Alexei A. Efros, and Jitendra Malik · 2017
Earlier work this paper cites.
Im2struct: Recovering 3d shape structure from a single rgb image
Chengjie Niu, Jun Li, and Kai Xu · 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.
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
Earlier work this paper cites.
Supervised Fitting of Geometric Primitives to 3D Point Clouds
Lingxiao Li, Minhyuk Sung, Anastasia Dubrovina, Li Yi, and Leonidas J Guibas · 2019
Earlier work this paper cites.
Superquadrics Revisited: Learning 3D Shape Parsing Beyond Cuboids
Despoina Paschalidou, Ali Osman Ulusoy, and Andreas Geiger · 2019
Earlier work this paper cites.
Partnet: A recursive part decomposition network for fine-grained and hierarchical shape segmentation
Fenggen Yu, Kun Liu, Yan Zhang, Chenyang Zhu, and Kai Xu · 2019
Earlier work this paper cites.
Bsp-net: Generating compact meshes via binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
Cited alongside, same era.
Cvxnet: Learnable convex decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, and Andrea Tagliasacchi · 2020
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Fame: 3d shape generation via functionality-aware model evolution
Yanran Guan, Han Liu, Kun Liu, Kangxue Yin, Ruizhen Hu, Oliver van Kaick, Yan Zhang, Ersin Yumer, Nathan Carr, Radomir Mech, et al · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
Despoina Paschalidou, Luc Van Gool, and Andreas Geiger · 2020
Cited alongside, same era.
Pie-net: Parametric inference of point cloud edges
Antoine Guédon and Vincent Lepetit · 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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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
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Neuralangelo: High-fidelity neural surface reconstruction
Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H Taylor, Mathias Unberath, Ming-Yu Liu, and Chen-Hsuan Lin · 2023
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Deformer: Integrating transformers with deformable models for 3d shape abstraction from a single image
Di Liu, Xiang Yu, Meng Ye, Qilong Zhangli, Zhuowei Li, Zhixing Zhang, and Dimitris N Metaxas · 2023
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Xiaogang Wang, Yuelang Xu, Kai Xu, Andrea Tagliasacchi, Bin Zhou, Ali Mahdavi-Amiri, and Hao Zhang · 2020
Cited alongside, same era.
BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks
Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, and Long Quan · 2020
Cited alongside, same era.
Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, and Yaron Lipman · 2020
Cited alongside, same era.
Adacoseg: Adaptive shape co-segmentation with group consistency loss
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Li Yi, Leonidas J Guibas, and Hao Zhang · 2020
Cited alongside, same era.
Neural parts: Learning expressive 3d shape abstractions with invertible neural networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger, and Sanja Fidler · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Star-tm: Structure aware reconstruction of textured mesh from single image
Tong Wu, Lin Gao, Ling-Xiao Zhang, Yu-Kun Lai, and Hao Zhang · 2021
Cited alongside, same era.
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Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans
Romain Loiseau, Elliot Vincent, Mathieu Aubry, and Loic Landrieu · 2023
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Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives
Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei A. Efros, and Mathieu Aubry · 2023
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Dpf-net: combining explicit shape priors in deformable primitive field for unsupervised structural reconstruction of 3d objects
Qingyao Shuai, Chi Zhang, Kaizhi Yang, and Xuejin Chen · 2023
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PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervision
Konstantinos Tertikas, Despoina Paschalidou, Boxiao Pan, Jeong Joon Park, Mikaela Angelina Uy, Ioannis Emiris, Yannis Avrithis, and Leonidas Guibas · 2023
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Cluster-guided contrastive graph clustering network
Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, and En Zhu · 2023
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Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning
Haiyang Ying, Yixuan Yin, Jinzhi Zhang, Fan Wang, Tao Yu, Ruqi Huang, and Lu Fang · 2023
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Fdc-nerf: learning pose-free neural radiance fields with flow-depth consistency
Huachen Gao, Shihe Shen, Zhe Zhang, Kaiqiang Xiong, Rui Peng, Zhirui Gao, Qi Wang, Yugui Xie, and Ronggang Wang · 2024
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2d gaussian splatting for geometrically accurate radiance fields
Binbin Huang, Zehao Yu, Anpei Chen, Andreas Geiger, and Shenghua Gao · 2024
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Gaussianblock: Building part-aware compositional and editable 3d scene by primitives and gaussians
Shuyi Jiang, Qihao Zhao, Hossein Rahmani, De Wen Soh, Jun Liu, and Na Zhao · 2024
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Garfield: Group anything with radiance fields
Chung Min* Kim, Mingxuan* Wu, Justin* Kerr, Matthew Tancik, Ken Goldberg, and Angjoo Kanazawa · 2024
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Games: Mesh-based adapting and modification of gaussian splatting
Joanna Waczyńska, Piotr Borycki, Sławomir Tadeja, Jacek Tabor, and Przemysław Spurek · 2024
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Gaussian grouping: Segment and edit anything in 3d scenes
Mingqiao Ye, Martin Danelljan, Fisher Yu, and Lei Ke · 2024
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Dpa-net: Structured 3d abstraction from sparse views via differentiable primitive assembly
Fenggen Yu, Yimin Qian, Xu Zhang, Francisca Gil-Ureta, Brian Jackson, Eric Bennett, and Hao Zhang · 2024
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Artiscene: Language-driven artistic 3d scene generation through image intermediary
Zeqi Gu, Yin Cui, Zhaoshuo Li, Fangyin Wei, Yunhao Ge, Jinwei Gu, Ming-Yu Liu, Abe Davis, and Yifan Ding · 2025
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Monomobility: Zero-shot 3d mobility analysis from monocular videos, 2025
Hongyi Zhou, Xiaogang Wang, Yulan Guo, and Kai Xu · 2025
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