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We present a real-time monocular dense SLAM system designed bottom-up from MASt3R, a two-view 3D reconstruction and matching prior.
A volumetric method for building complex models from range images
Brian Curless and Marc Levoy · 1996
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Multiple view geometry in computer vision
Richard Hartley and Andrew Zisserman · 2003
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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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Parallel tracking and mapping for small AR workspaces
Georg Klein and David Murray · 2007
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Generic camera calibration and modeling using spline surfaces
Dennis Rosebrock and Friedrich M. Wahl · 2012
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A benchmark for the evaluation of RGB-D SLAM systems
Jürgen Sturm, Nikolas Engelhard, Felix Endres, Wolfram Burgard, and Daniel Cremers · 2012
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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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To aggregate or not to aggregate: Selective match kernels for image search
Giorgos Tolias, Yannis Avrithis, and Hervé Jégou · 2013
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Dense scene reconstruction with points of interest
Qian-Yi Zhou and Vladlen Koltun · 2013
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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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Constant-time monocular self-calibration
Nima Keivan and Gabe Sibley · 2014
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ORB-SLAM: A versatile and accurate monocular SLAM system
Raúl Mur-Artal, J. M. M. Montiel, and Juan D. Tardós · 2015
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Designing deep networks for surface normal estimation
Xiaolong Wang, David Fouhey, and Abhinav Gupta · 2015
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The EuRoC micro aerial vehicle datasets
Michael Burri, Janosch Nikolic, Pascal Gohl, Thomas Schneider, Joern Rehder, Sammy Omari, Markus W. Achtelik, and Roland Siegwart · 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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A micro lie theory for state estimation in robotics
Joan Sola, Jeremie Deray, and Dinesh Atchuthan · 2018
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DeepTAM: Deep tracking and mapping
H. Zhou, B. Ummenhofer, and T. Brox · 2018
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BAD SLAM: Bundle adjusted direct RGB-D SLAM
Thomas Schöps, Torsten Sattler, and Marc Pollefeys · 2019
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BA-Net: Dense bundle adjustment networks
Chengzhou Tang and Ping Tan · 2019
Cited alongside, same era.
DeepFactors: Real-time probabilistic dense monocular SLAM
Jan Czarnowski, Tristan Laidlow, Ronald Clark, and Andrew J. Davison · 2020
Cited alongside, same era.
NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Atlas: End-to-end 3D scene reconstruction from posed images
Zak Murez, Tarrence van As, James Bartolozzi, Ayan Sinha, Vijay Badrinarayanan, and Andrew Rabinovich · 2020
Cited alongside, same era.
Why having 10,000 parameters in your camera model is better than twelve
Thomas Schöps, Viktor Larsson, Marc Pollefeys, and Torsten Sattler · 2020
Cited alongside, same era.
Learning and aggregating deep local descriptors for instance-level recognition
GO-SLAM: Global optimization for consistent 3D instant reconstruction
Youmin Zhang, Fabio Tosi, Stefano Mattoccia, and Matteo Poggi · 2023
Later among the works it cites.
Rethinking inductive biases for surface normal estimation
Gwangbin Bae and Andrew J. Davison · 2024
Closest in time.
COMO: Compact mapping and odometry
Eric Dexheimer and Andrew J. Davison · 2024
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MASt3R-SfM: a fully-integrated solution for unconstrained structure-from-motion
Bardienus Duisterhof, Lojze Zust, Philippe Weinzaepfel, Vincent Leroy, Yohann Cabon, and Jerome Revaud · 2024
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Repurposing diffusion-based image generators for monocular depth estimation
Bingxin Ke, Anton Obukhov, Shengyu Huang, Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2024
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SplaTAM: Splat, track & map 3D Gaussians for dense RGB-D SLAM
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Giorgos Tolias, Tomas Jenicek, and Ondřej Chum · 2020
Cited alongside, same era.
ORB-SLAM3: An accurate open-source library for visual, visual–inertial, and multimap SLAM
Carlos Campos, Richard Elvira, Juan J. Gómez Rodríguez, José M. M. Montiel, and Juan D. Tardós · 2021
Cited alongside, same era.
iMAP: Implicit mapping and positioning in real-time
Edgar Sucar, Shikun Liu, Joseph Ortiz, and Andrew J. Davison · 2021
Cited alongside, same era.
NeuralRecon: Real-time coherent 3D reconstruction from monocular video
Jiaming Sun, Yiming Xie, Linghao Chen, Xiaowei Zhou, and Hujun Bao · 2021
Cited alongside, same era.
TANDEM: Tracking and dense mapping in real-time using deep multi-view stereo
Lukas Koestler, Nan Yang, Niclas Zeller, and Daniel Cremers · 2022
Cited alongside, same era.
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
Rene Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2022
Cited alongside, same era.
SimpleRecon: 3D reconstruction without 3D convolutions
Mohamed Sayed, John Gibson, Jamie Watson, Victor Prisacariu, Michael Firman, and Clément Godard · 2022
Cited alongside, same era.
Nikhil Keetha, Jay Karhade, Krishna Murthy Jatavallabhula, Gengshan Yang, Sebastian Scherer, Deva Ramanan, and Jonathon Luiten · 2024
Closest in time.
Grounding image matching in 3D with MASt3R
Vincent Leroy, Yohann Cabon, and Jerome Revaud · 2024
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Deep patch visual SLAM
Lahav Lipson, Zachary Teed, and Jia Deng · 2024
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Gaussian splatting SLAM
Hidenobu Matsuki, Riku Murai, Paul H. J. Kelly, and Andrew J. Davison · 2024
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SuperPrimitive: Scene reconstruction at a primitive level
Kirill Mazur, Gwangbin Bae, and Andrew J. Davison · 2024
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Global structure-from-motion revisited
Linfei Pan, Daniel Barath, Marc Pollefeys, and Johannes Lutz Schönberger · 2024
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GeoCalib: Single-image calibration with geometric optimization
Alexander Veicht, Paul-Edouard Sarlin, Philipp Lindenberger, and Marc Pollefeys · 2024
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3D reconstruction with spatial memory
Hengyi Wang and Lourdes Agapito · 2024
Closest in time.
DUSt3R: Geometric 3D vision made easy
Shuzhe Wang, Vincent Leroy, Yohann Cabon, Boris Chidlovskii, and Jerome Revaud · 2024
Closest in time.
GS-SLAM: Dense visual SLAM with 3D Gaussian splatting
Chi Yan, Delin Qu, Dan Xu, Bin Zhao, Zhigang Wang, Dong Wang, and Xuelong Li · 2024
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Depth anything: Unleashing the power of large-scale unlabeled data
Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
Closest in time.
NICER-SLAM: Neural implicit scene encoding for RGB SLAM
Zihan Zhu, Songyou Peng, Viktor Larsson, Zhaopeng Cui, Martin R Oswald, Andreas Geiger, and Marc Pollefeys · 2024
Closest in time.