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3D reconstruction has lately attracted increasing attention due to its wide application in many areas, such as autonomous driving, robotics and virtual reality.
A multiple-baseline stereo
Masatoshi Okutomi and Takeo Kanade · 1993
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Robert T Collins · 1996
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Heiko Hirschmuller · 2007
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Accurate, dense, and robust multiview stereopsis
Yasutaka Furukawa and Jean Ponce · 2009
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Screened poisson surface reconstruction
Michael Kazhdan and Hugues Hoppe · 2013
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Massively parallel multiview stereopsis by surface normal diffusion
Silvano Galliani, Katrin Lasinger, and Konrad Schindler · 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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Large-scale data for multiple-view stereopsis
Henrik Aanæs, Rasmus Ramsbøl Jensen, George Vogiatzis, Engin Tola, and Anders Bjorholm Dahl · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
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Structure-from-motion revisited
Johannes L Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes L Schönberger, Enliang Zheng, Jan-Michael Frahm, and Marc Pollefeys · 2016
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Arno Knapitsch, Jaesik Park, Qian-Yi Zhou, and Vladlen Koltun · 2017
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A multi-view stereo benchmark with high-resolution images and multi-camera videos
Thomas Schöps, Johannes L Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger · 2017
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Dpsnet: End-to-end deep plane sweep stereo
Deep stereo using adaptive thin volume representation with uncertainty awareness
Shuo Cheng, Zexiang Xu, Shilin Zhu, Zhuwen Li, Li Erran Li, Ravi Ramamoorthi, and Hao Su · 2020
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Cascade cost volume for high-resolution multi-view stereo and stereo matching
Xiaodong Gu, Zhiwen Fan, Siyu Zhu, Zuozhuo Dai, Feitong Tan, and Ping Tan · 2020
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Normal assisted stereo depth estimation
Uday Kusupati, Shuo Cheng, Rui Chen, and Hao Su · 2020
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Depth-map completion for large indoor scene reconstruction
Hongmin Liu, Xincheng Tang, and Shuhan Shen · 2020
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Dense hybrid recurrent multi-view stereo net with dynamic consistency checking
Jianfeng Yan, Zizhuang Wei, Hongwei Yi, Mingyu Ding, Runze Zhang, Yisong Chen, Guoping Wang, and Yu-Wing Tai · 2020
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Cost volume pyramid based depth inference for multi-view stereo
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Sunghoon Im, Hae-Gon Jeon, Stephen Lin, and In So Kweon · 2018
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao Yao, Zixin Luo, Shiwei Li, Tian Fang, and Long Quan · 2018
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Point-based multi-view stereo network
Rui Chen, Songfang Han, Jing Xu, and Hao Su · 2019
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Recurrent mvsnet for high-resolution multi-view stereo depth inference
Yao Yao, Zixin Luo, Shiwei Li, Tianwei Shen, Tian Fang, and Long Quan · 2019
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Free-form image inpainting with gated convolution
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2019
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Jiayu Yang, Wei Mao, Jose M Alvarez, and Miaomiao Liu · 2020
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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
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Pyramid multi-view stereo net with self-adaptive view aggregation
Hongwei Yi, Zizhuang Wei, Mingyu Ding, Runze Zhang, Yisong Chen, Guoping Wang, and Yu-Wing Tai · 2020
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Visibility-aware multi-view stereo network
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, and Tian Fang · 2020
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Aa-rmvsnet: Adaptive aggregation recurrent multi-view stereo network
Zizhuang Wei, Qingtian Zhu, Chen Min, Yisong Chen, and Guoping Wang · 2021
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