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In this paper, we propose a pipeline to generate 3D point cloud of an object from a single-view RGB image.
Least-squares meshes
Olga Sorkine and Daniel Cohen-Or · 2004
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Laplacian mesh optimization
Andrew Nealen, Takeo Igarashi, Olga Sorkine, and Marc Alexa · 2006
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Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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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
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Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs
Bo Li, Chunhua Shen, Yuchao Dai, Anton Van Den Hengel, and Mingyi He · 2015
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Designing deep networks for surface normal estimation
Xiaolong Wang, David Fouhey, and Abhinav Gupta · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age
Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, José Neira, Ian Reid, and John J Leonard · 2016
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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
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Deeper depth prediction with fully convolutional residual networks
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab · 2016
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2016
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Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
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A field model for repairing 3d shapes
Duc Thanh Nguyen, Binh-Son Hua, Khoi Tran, Quang-Hieu Pham, and Sai-Kit Yeung · 2016
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Estimating depth from monocular images as classification using deep fully convolutional residual networks
Yuanzhouhan Cao, Zifeng Wu, and Chunhua Shen · 2017
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A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
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Unsupervised monocular depth estimation with left-right consistency
Clément Godard, Oisin Mac Aodha, and Gabriel J Brostow · 2017
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Weakly supervised 3d reconstruction with adversarial constraint
JunYoung Gwak, Christopher B Choy, Manmohan Chandraker, Animesh Garg, and Silvio Savarese · 2017
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Hierarchical surface prediction for 3d object reconstruction
Three for one and one for three: Flow, segmentation, and surface normals
Hoang-An Le, Anil S Baslamisli, Thomas Mensink, and Theo Gevers · 2018
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Priyanka Mandikal, Navaneet Murthy, Mayank Agarwal, and R Venkatesh Babu · 2018
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Matryoshka networks: Predicting 3d geometry via nested shape layers
Stephan R Richter and Stefan Roth · 2018
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Pix3d: Dataset and methods for single-image 3d shape modeling
Xingyuan Sun, Jiajun Wu, Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Tianfan Xue, Joshua B Tenenbaum, and William T Freeman · 2018
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Multi-view consistency as supervisory signal for learning shape and pose prediction
Shubham Tulsiani, Alexei A Efros, and Jitendra Malik · 2018
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Christian Häne, Shubham Tulsiani, and Jitendra Malik · 2017
Cited alongside, same era.
Semi-supervised deep learning for monocular depth map prediction
Yevhen Kuznietsov, Jörg Stückler, and Bastian Leibe · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2017
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Marrnet: 3d shape reconstruction via 2.5 d sketches
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, and Josh Tenenbaum · 2017
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3d object reconstruction from a single depth view with adversarial learning
Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, and Niki Trigoni · 2017
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3dcontextnet: Kd tree guided hierarchical learning of point clouds using local contextual cues
Wei Zeng and Theo Gevers · 2017
Cited alongside, same era.
Pixel2mesh: Generating 3d mesh models from single rgb images
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
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Pcn: Point completion network
Wentao Yuan, Tejas Khot, David Held, Christoph Mertz, and Martial Hebert · 2018
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Learning to reconstruct shapes from unseen classes
Xiuming Zhang, Zhoutong Zhang, Bill Freeman, and Jiajun Wu · 2018
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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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Graphx-convolution for point cloud deformation in 2d-to-3d conversion
Anh-Duc Nguyen, Seonghwa Choi, Woojae Kim, and Sanghoon Lee · 2019
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Efficient learning on point clouds with basis point sets
Sergey Prokudin, Christoph Lassner, and Javier Romero · 2019
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