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We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes.
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D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black · 2012
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Jakob Engel, Thomas Schöps, and Daniel Cremers · 2014
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Orb-slam: a versatile and accurate monocular slam system
Raul Mur-Artal, Jose Maria Martinez Montiel, and Juan D Tardos · 2015
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
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Johannes L Schönberger, Enliang Zheng, Jan-Michael Frahm, and Marc Pollefeys · 2016
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Jakob Engel, Vladlen Koltun, and Daniel Cremers · 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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Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Alex Kendall and Yarin Gal · 2017
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Sen Wang, Ronald Clark, Hongkai Wen, and Niki Trigoni · 2017
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Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, and Andrew J Davison · 2018
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Megadepth: Learning single-view depth prediction from internet photos
Zhengqi Li and Noah Snavely · 2018
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Hippolyt Ritter, Aleksandar Botev, and David Barber · 2018
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Chengzhou Tang and Ping Tan · 2018
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Zhengqi Li, Tali Dekel, Forrester Cole, Richard Tucker, Noah Snavely, Ce Liu, and William T Freeman · 2019
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Structure from motion for panorama-style videos
Chris Sweeney, Aleksander Holynski, Brian Curless, and Steve M Seitz · 2019
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Deepfactors: Real-time probabilistic dense monocular slam
Jan Czarnowski, Tristan Laidlow, Ronald Clark, and Andrew J Davison · 2020
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Reducing drift in structure from motion using extended features
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Particlesfm: Exploiting dense point trajectories for localizing moving cameras in the wild
Wang Zhao, Shaohui Liu, Hengkai Guo, Wenping Wang, and Yong-Jin Liu · 2022
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Deep geometry-aware camera self-calibration from video
Annika Hagemann, Moritz Knorr, and Christoph Stiller · 2023
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Dynibar: Neural dynamic image-based rendering
Zhengqi Li, Qianqian Wang, Forrester Cole, Richard Tucker, and Noah Snavely · 2023
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Robust dynamic radiance fields
Yu-Lun Liu, Chen Gao, Andreas Meuleman, Hung-Yu Tseng, Ayush Saraf, Changil Kim, Yung-Yu Chuang, Johannes Kopf, and Jia-Bin Huang · 2023
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Camp: Camera preconditioning for neural radiance fields
Keunhong Park, Philipp Henzler, Ben Mildenhall, Jonathan T Barron, and Ricardo Martin-Brualla · 2023
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Dytanvo: Joint refinement of visual odometry and motion segmentation in dynamic environments
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René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Tartanair: A dataset to push the limits of visual slam
Wenshan Wang, Delong Zhu, Xiangwei Wang, Yaoyu Hu, Yuheng Qiu, Chen Wang, Yafei Hu, Ashish Kapoor, and Sebastian Scherer · 2020
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D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry
Nan Yang, Lukas von Stumberg, Rui Wang, and Daniel Cremers · 2020
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Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam
Carlos Campos, Richard Elvira, Juan J Gómez Rodríguez, José MM Montiel, and Juan D Tardós · 2021
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Robust consistent video depth estimation
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Shihao Shen, Yilin Cai, Wenshan Wang, and Sebastian Scherer · 2023
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Neural video depth stabilizer
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Metric3d: Towards zero-shot metric 3d prediction from a single image
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