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Visual odometry estimates the motion of a moving camera based on visual input.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
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Object recognition from local scale-invariant features
David G Lowe · 1999
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Bundle adjustment—a modern synthesis
Bill Triggs, Philip F McLauchlan, Richard I Hartley, and Andrew W Fitzgibbon · 1999
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Monoslam: Real-time single camera slam
Andrew J Davison, Ian D Reid, Nicholas D Molton, and Olivier Stasse · 2007
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A naturalistic open source movie for optical flow evaluation
D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Lsd-slam: Large-scale direct monocular slam
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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An overview to visual odometry and visual slam: Applications to mobile robotics
Khalid Yousif, Alireza Bab-Hadiashar, and Reza Hoseinnezhad · 2015
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Streaming and exploration of dynamically changing dense 3d reconstructions in immersive virtual reality
Annette Mossel and Manuel Kroeter · 2016
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Direct sparse odometry
Jakob Engel, Vladlen Koltun, and Daniel Cremers · 2017
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ORB-SLAM2: an open-source SLAM system for monocular, stereo and RGB-D cameras
Raúl Mur-Artal and Juan D. Tardós · 2017
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Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
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Dynaslam: Tracking, mapping, and inpainting in dynamic scenes
Berta Bescos, José M Fácil, Javier Civera, and José Neira · 2018
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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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Video object segmentation with language referring expressions
Anna Khoreva, Anna Rohrbach, and Bernt Schiele · 2018
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Geonet: Unsupervised learning of dense depth, optical flow and camera pose
Zhichao Yin and Jianping Shi · 2018
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Self-supervised learning with geometric constraints in monocular video: Connecting flow, depth, and camera
Yuhua Chen, Cordelia Schmid, and Cristian Sminchisescu · 2019
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Competitive collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation
Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, and Michael J Black · 2019
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The replica dataset: A digital replica of indoor spaces
Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, et al · 2019
Cited alongside, same era.
Deepv2d: Video to depth with differentiable structure from motion
Zachary Teed and Jia Deng · 2019
Cited alongside, same era.
Space-time correspondence as a contrastive random walk
Allan Jabri, Andrew Owens, and Alexei Efros · 2020
Cited alongside, same era.
Airdos: Dynamic slam benefits from articulated objects
Yuheng Qiu, Chen Wang, Wenshan Wang, Mina Henein, and Sebastian Scherer · 2022
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Structure and motion from casual videos
Zhoutong Zhang, Forrester Cole, Zhengqi Li, Michael Rubinstein, Noah Snavely, and William T Freeman · 2022
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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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Context-tap: Tracking any point demands spatial context features
Weikang Bian, Zhaoyang Huang, Xiaoyu Shi, Yitong Dong, Yijin Li, and Hongsheng Li · 2023
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Uncertainty-driven dense two-view structure from motion
Weirong Chen, Suryansh Kumar, and Fisher Yu · 2023
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Self-supervised deep visual odometry with online adaptation
Shunkai Li, Xin Wang, Yingdian Cao, Fei Xue, Zike Yan, and Hongbin Zha · 2020
Cited alongside, same era.
Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
Cited alongside, same era.
D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry
Nan Yang, Lukas von Stumberg, Rui Wang, and Daniel Cremers · 2020
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Cited alongside, same era.
Robust consistent video depth estimation
Johannes Kopf, Xuejian Rong, and Jia-Bin Huang · 2021
Cited alongside, same era.
Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Zachary Teed and Jia Deng · 2021
Cited alongside, same era.
Neuraldiff: Segmenting 3d objects that move in egocentric videos
Vadim Tschernezki, Diane Larlus, and Andrea Vedaldi · 2021
Cited alongside, same era.
Tapir: Tracking any point with per-frame initialization and temporal refinement
Carl Doersch, Yi Yang, Mel Vecerik, Dilara Gokay, Ankush Gupta, Yusuf Aytar, Joao Carreira, and Andrew Zisserman · 2023
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Cotracker: It is better to track together
Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, and Christian Rupprecht · 2023
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Dytanvo: Joint refinement of visual odometry and motion segmentation in dynamic environments
Shihao Shen, Yilin Cai, Wenshan Wang, and Sebastian Scherer · 2023
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Tracking everything everywhere all at once
Qianqian Wang, Yen-Yu Chang, Ruojin Cai, Zhengqi Li, Bharath Hariharan, Aleksander Holynski, and Noah Snavely · 2023
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Emernerf: Emergent spatial-temporal scene decomposition via self-supervision
Jiawei Yang, Boris Ivanovic, Or Litany, Xinshuo Weng, Seung Wook Kim, Boyi Li, Tong Che, Danfei Xu, Sanja Fidler, Marco Pavone, et al · 2023
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Pvo: Panoptic visual odometry
Weicai Ye, Xinyue Lan, Shuo Chen, Yuhang Ming, Xingyuan Yu, Hujun Bao, Zhaopeng Cui, and Guofeng Zhang · 2023
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Pointodyssey: A large-scale synthetic dataset for long-term point tracking
Yang Zheng, Adam W Harley, Bokui Shen, Gordon Wetzstein, and Leonidas J Guibas · 2023
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Bootstap: Bootstrapped training for tracking-any-point
Carl Doersch, Yi Yang, Dilara Gokay, Pauline Luc, Skanda Koppula, Ankush Gupta, Joseph Heyward, Ross Goroshin, João Carreira, and Andrew Zisserman · 2024
Closest in time.
Deep patch visual odometry
Zachary Teed, Lahav Lipson, and Jia Deng · 2024
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Dino-tracker: Taming dino for self-supervised point tracking in a single video
Narek Tumanyan, Assaf Singer, Shai Bagon, and Tali Dekel · 2024
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Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks
Sen Wang, Ronald Clark, Hongkai Wen, and Niki Trigoni · 2050
Closest in time.