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The efficient fusion of depth maps is a key part of most state-of-the-art 3D reconstruction methods.
A volumetric method for building complex models from range images
Brian Curless and Marc Levoy · 1996
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A globally optimal algorithm for robust tv-l1 range image integration
Christopher Zach, Thomas Pock, and Horst Bischof · 2007
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Fast and high quality fusion of depth maps
Christopher Zach · 2008
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Continuous global optimization in multiview 3d reconstruction
Kalin Kolev, Maria Klodt, Thomas Brox, and Daniel Cremers · 2009
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Fusion of depth maps with multiple scales
Simon Fuhrmann and Michael Goesele · 2011
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Kinectfusion: real-time dynamic 3d surface reconstruction and interaction
Shahram Izadi, Richard A. Newcombe, David Kim, Otmar Hilliges, David Molyneaux, Steve Hodges, Pushmeet Kohli, Jamie Shotton, Andrew J. Davison, and Andrew W. Fitzgibbon · 2011
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Probabilistic depth map fusion for real-time multi-view stereo
Yong Duan, Mingtao Pei, and Yunde Jia · 2012
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A generative model for online depth fusion
Oliver J. Woodford and George Vogiatzis · 2012
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Joint 3d scene reconstruction and class segmentation
Christian Häne, Christopher Zach, Andrea Cohen, Roland Angst, and Marc Pollefeys · 2013
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Real-time 3d reconstruction in dynamic scenes using point-based fusion
Maik Keller, Damien Lefloch, Martin Lambers, Shahram Izadi, Tim Weyrich, and Andreas Kolb · 2013
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Real-time 3d reconstruction at scale using voxel hashing
Matthias Nießner, Michael Zollhöfer, Shahram Izadi, and Marc Stamminger · 2013
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Scene coordinate regression forests for camera relocalization in rgb-d images
Jamie Shotton, Ben Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, and Andrew Fitzgibbon · 2013
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Large-scale multi-resolution surface reconstruction from RGB-D sequences
Frank Steinbrücker, Christian Kerl, and Daniel Cremers · 2013
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Point-based 3d reconstruction of thin objects
Benjamin Ummenhofer and Thomas Brox · 2013
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Dense scene reconstruction with points of interest
Qian-Yi Zhou and Vladlen Koltun · 2013
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Multi-resolution surfel maps for efficient dense 3d modeling and tracking
Jörg Stückler and Sven Behnke · 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, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Robust reconstruction of indoor scenes
Sungjoon Choi, Qian-Yi Zhou, and Vladlen Koltun · 2015
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Very high frame rate volumetric integration of depth images on mobile devices
Olaf Kähler, Victor Adrian Prisacariu, Carl Yuheng Ren, Xin Sun, Philip H. S. Torr, and David W. Murray · 2015
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Anisotropic point-based fusion
Damien Lefloch, Tim Weyrich, and Andreas Kolb · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Discrete optimization of ray potentials for semantic 3d reconstruction
Nikolay Savinov, Lubor Ladicky, Christian Hane, and Marc Pollefeys · 2015
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Towards probabilistic volumetric reconstruction using ray potentials
Ali Osman Ulusoy, Andreas Geiger, and Michael J. Black · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, S. Song, A. Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and J. Xiao · 2015
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Shading-based refinement on volumetric signed distance functions
Michael Zollhöfer, Angela Dai, Matthias Innmann, Chenglei Wu, Marc Stamminger, Christian Theobalt, and Matthias Nießner · 2015
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Large-scale semantic 3d reconstruction: an adaptive multi-resolution model for multi-class volumetric labeling
Maroš Bláha, Christoph Vogel, Audrey Richard, Jan D. Wegner, Thomas Pock, and Konrad Schindler · 2016
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Multi-label semantic 3d reconstruction using voxel blocks
Ian Cherabier, Christian Häne, Martin R. Oswald, and Marc Pollefeys · 2016
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Codeslam - learning a compact, optimisable representation for dense visual SLAM
Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, and Andrew J. Davison · 2018
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Learning to reconstruct high-quality 3d shapes with cascaded fully convolutional networks
Yan-Pei Cao, Zheng-Ning Liu, Zheng-Fei Kuang, Leif Kobbelt, and Shi-Min Hu · 2018
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Learning priors for semantic 3d reconstruction
Ian Cherabier, Johannes L. Schönberger, Martin R. Oswald, Marc Pollefeys, and Andreas Geiger · 2018
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3dmv: Joint 3d-multi-view prediction for 3d semantic scene segmentation
Angela Dai and Matthias Nießner · 2018
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Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans
Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, and Matthias Nießner · 2018
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Olaf Kähler, Victor Adrian Prisacariu, Julien P. C. Valentin, and David W. Murray · 2016
Cited alongside, same era.
A median-based depthmap fusion strategy for the generation of oriented points
M. Rothermel, N. Haala, and D. Fritsch · 2016
Cited alongside, same era.
Semantic 3d reconstruction with continuous regularization and ray potentials using a visibility consistency constraint
Nikolay Savinov, Christian Häne, Lubor Ladicky, and Marc Pollefeys · 2016
Cited alongside, same era.
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
Cited alongside, same era.
Patches, planes and probabilities: A non-local prior for volumetric 3d reconstruction
Ali Osman Ulusoy, Michael J. Black, and Andreas Geiger · 2016
Cited alongside, same era.
Elasticfusion: Real-time dense SLAM and light source estimation
Thomas Whelan, Renato F. Salas-Moreno, Ben Glocker, Andrew J. Davison, and Stefan Leutenegger · 2016
Cited alongside, same era.
Psdf fusion: Probabilistic signed distance function for on-the-fly 3d data fusion and scene reconstruction
Wei Dong, Qiuyuan Wang, Xin Wang, and Hongbin Zha · 2018
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Atlasnet: A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, and Mathieu Aubry · 2018
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Shape reconstruction using volume sweeping and learned photoconsistency
Vincent Leroy, Jean-Sébastien Franco, and Edmond Boyer · 2018
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Real-time variational range image fusion and visualization for large-scale scenes using GPU hash tables
Nico Marniok and Bastian Goldluecke · 2018
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Raynet: Learning volumetric 3d reconstruction with ray potentials
Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt, Luc Van Gool, and Andreas Geiger · 2018
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Accurate 3-d reconstruction with rgb-d cameras using depth map fusion and pose refinement
Markus Ylimäki, Juho Kannala, and Janne Heikkilä · 2018
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Deeptam: Deep tracking and mapping
Huizhong Zhou, Benjamin Ummenhofer, and Thomas Brox · 2018
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State of the Art on 3D Reconstruction with RGB-D Cameras
M. Zollhöfer, P. Stotko, A. Görlitz, C. Theobalt, M. Nießner, R. Klein, and A. Kolb · 2018
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Learning non-volumetric depth fusion using successive reprojections
Simon Donné and Andreas Geiger · 2019
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Mesh r-cnn
Georgia Gkioxari, Jitendra Malik, and Justin Johnson · 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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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Surfelmeshing: Online surfel-based mesh reconstruction
Thomas Schöps, Torsten Sattler, and Marc Pollefeys · 2019
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Pixel2mesh++: Multi-view 3d mesh generation via deformation
Chao Wen, Yinda Zhang, Zhuwen Li, and Yanwei Fu · 2019
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Scenecode: Monocular dense semantic reconstruction using learned encoded scene representations
Shuaifeng Zhi, Michael Bloesch, Stefan Leutenegger, and Andrew J. Davison · 2019
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