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We present Any4D, a scalable multi-view transformer for metric-scale, dense feed-forward 4D reconstruction.
Bundle adjustment—a modern synthesis
Bill Triggs, Philip F McLauchlan, Richard I Hartley, and Andrew W Fitzgibbon · 1999
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Three-dimensional scene flow
Sundar Vedula, Simon Baker, Peter Rander, Robert Collins, and Takeo Kanade · 1999
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Particle video: Long-range motion estimation using point trajectories
P. Sand and S. Teller · 2006
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A comparison and evaluation of multi-view stereo reconstruction algorithms
Steven M Seitz, Brian Curless, James Diebel, Daniel Scharstein, and Richard Szeliski · 2006
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A variational method for scene flow estimation from stereo sequences
Frédéric Huguet and Frédéric Devernay · 2007
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Parallel tracking and mapping for small ar workspaces
Georg Klein and David Murray · 2007
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Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score
Jean-Philippe Pons, Renaud Keriven, and Olivier Faugeras · 2007
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Building rome in a day
Sameer Agarwal, Noah Snavely, Ian Simon, Steven M. Seitz, and Richard Szeliski · 2009
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Multi-view scene flow estimation: A view centered variational approach
Tali Basha, Yael Moses, and Nahum Kiryati · 2013
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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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Object scene flow for autonomous vehicles
Moritz Menze and Andreas Geiger · 2015
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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 Schonberger and Jan-Michael Frahm · 2016
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Factor graphs for robot perception
Frank Dellaert, Michael Kaess, et al · 2017
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Monocular dense 3d reconstruction of a complex dynamic scene from two perspective frames
Suryansh Kumar, Yuchao Dai, and Hongdong Li · 2017
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Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras
Raul Mur-Artal and Juan D Tardós · 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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Megadepth: Learning single-view depth prediction from internet photos
Zhengqi Li and Noah Snavely · 2018
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Flownet3d: Learning scene flow in 3d point clouds
Xingyu Liu, Charles R Qi, and Leonidas J Guibas · 2019
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Refusion: 3d reconstruction in dynamic environments for rgb-d cameras exploiting residuals
Emanuele Palazzolo, Jens Behley, Philipp Lottes, Philippe Giguere, and Cyrill Stachniss · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
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Mapillary planet-scale depth dataset
Manuel López Antequera, Pau Gargallo, Markus Hofinger, Samuel Rota Bulo, Yubin Kuang, and Peter Kontschieder · 2020
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Yohann Cabon, Naila Murray, and Martin Humenberger · 2020
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Dynamic slam: The need for speed
Mina Henein, Jun Zhang, Robert Mahony, and Viorela Ila · 2020
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Just go with the flow: Self-supervised scene flow estimation
Himangi Mittal, Brian Okorn, and David Held · 2020
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FLOT: Scene Flow on Point Clouds Guided by Optimal Transport
Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Pointpwc-net: Cost volume on point clouds for (self-) supervised scene flow estimation
Wenxuan Wu, Zhi Yuan Wang, Zhuwen Li, Wei Liu, and Li Fuxin · 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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Sail-vos 3d: A synthetic dataset and baselines for object detection and 3d mesh reconstruction from video data
Grounding image matching in 3d with mast3r
Vincent Leroy, Yohann Cabon, and Jérôme Revaud · 2024
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Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos
Zhengqi Li, Richard Tucker, Forrester Cole, Qianqian Wang, Linyi Jin, Vickie Ye, Angjoo Kanazawa, Aleksander Holynski, and Noah Snavely · 2024
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Delta: Dense efficient long-range 3d tracking for any video
Tuan Duc Ngo, Peiye Zhuang, Chuang Gan, Evangelos Kalogerakis, Sergey Tulyakov, Hsin-Ying Lee, and Chaoyang Wang · 2024
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L4gm: Large 4d gaussian reconstruction model
Jiawei Ren, Kevin Xie, Ashkan Mirzaei, Hanxue Liang, Xiaohui Zeng, Karsten Kreis, Ziwei Liu, Antonio Torralba, Sanja Fidler, Seung Wook Kim, and Huan Ling · 2024
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Yuan-Ting Hu, Jiahong Wang, Raymond A Yeh, and Alexander G Schwing · 2021
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Robust consistent video depth estimation
Johannes Kopf, Xuejian Rong, and Jia-Bin Huang · 2021
Cited alongside, same era.
Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
Cited alongside, same era.
Compositional and scalable object slam
Akash Sharma, Wei Dong, and Michael Kaess · 2021
Cited alongside, same era.
Particle video revisited: Tracking through occlusions using point trajectories
Adam W Harley, Zhaoyuan Fang, and Katerina Fragkiadaki · 2022
Cited alongside, same era.
Airdos: Dynamic slam benefits from articulated objects
Yuheng Qiu, Chen Wang, Wenshan Wang, Mina Henein, and Sebastian Scherer · 2022
Cited alongside, same era.
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2022
Cited alongside, same era.
Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, and Joachim Pehserl · 2024
Later among the works it cites.
Cat4d: Create anything in 4d with multi-view video diffusion models
Rundi Wu, Ruiqi Gao, Ben Poole, Alex Trevithick, Changxi Zheng, Jonathan T Barron, and Aleksander Holynski · 2024
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Spatialtracker: Tracking any 2d pixels in 3d space
Yuxi Xiao, Qianqian Wang, Shangzhan Zhang, Nan Xue, Sida Peng, Yujun Shen, and Xiaowei Zhou · 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
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Monst3r: A simple approach for estimating geometry in the presence of motion
Junyi Zhang, Charles Herrmann, Junhwa Hur, Varun Jampani, Trevor Darrell, Forrester Cole, Deqing Sun, and Ming-Hsuan Yang · 2024
Later among the works it cites.
Rayst3r: Predicting novel depth maps for zero-shot object completion
Bardienus P Duisterhof, Jan Oberst, Bowen Wen, Stan Birchfield, Deva Ramanan, and Jeffrey Ichnowski · 2025
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St4rtrack: Simultaneous 4d reconstruction and tracking in the world
Haiwen Feng, Junyi Zhang, Qianqian Wang, Yufei Ye, Pengcheng Yu, Michael J Black, Trevor Darrell, and Angjoo Kanazawa · 2025
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Depthcrafter: Generating consistent long depth sequences for open-world videos
Wenbo Hu, Xiangjun Gao, Xiaoyu Li, Sijie Zhao, Xiaodong Cun, Yong Zhang, Long Quan, and Ying Shan · 2025
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Understanding dynamic scenes in ego centric 4d point clouds
Junsheng Huang, Shengyu Hao, Bocheng Hu, and Gaoang Wang · 2025
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Pow3r: Empowering unconstrained 3d reconstruction with camera and scene priors
Wonbong Jang, Philippe Weinzaepfel, Vincent Leroy, Lourdes Agapito, and Jerome Revaud · 2025
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Mosca: Dynamic gaussian fusion from casual videos via 4d motion scaffolds
Jiahui Lei, Yijia Weng, Adam W Harley, Leonidas Guibas, and Kostas Daniilidis · 2025
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Movies: Motion-aware 4d dynamic view synthesis in one second
Chenguo Lin, Yuchen Lin, Panwang Pan, Yifan Yu, Honglei Yan, Katerina Fragkiadaki, and Yadong Mu · 2025
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4dtam: Non-rigid tracking and mapping via dynamic surface gaussians
Hidenobu Matsuki, Gwangbin Bae, and Andrew J Davison · 2025
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Pre-training auto-regressive robotic models with 4d representations
Dantong Niu, Yuvan Sharma, Haoru Xue, Giscard Biamby, Junyi Zhang, Ziteng Ji, Trevor Darrell, and Roei Herzig · 2025
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Dynomo: Online point tracking by dynamic online monocular gaussian reconstruction
Jenny Seidenschwarz, Qunjie Zhou, Bardienus P Duisterhof, Deva Ramanan, and Laura Leal-Taixé · 2025
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Dynamic point maps: A versatile representation for dynamic 3d reconstruction
Edgar Sucar, Zihang Lai, Eldar Insafutdinov, and Andrea Vedaldi · 2025
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BEDLAM2.0: Synthetic humans and cameras in motion
Joachim Tesch, Giorgio Becherini, Prerana Achar, Anastasios Yiannakidis, Muhammed Kocabas, Priyanka Patel, and Michael J. Black · 2025
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Spatialtrackerv2: 3d point tracking made easy
Yuxi Xiao, Jianyuan Wang, Nan Xue, Nikita Karaev, Iurii Makarov, Bingyi Kang, Xin Zhu, Hujun Bao, Yujun Shen, and Xiaowei Zhou · 2025
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Llava-4d: Embedding spatiotemporal prompt into lmms for 4d scene understanding
Hanyu Zhou and Gim Hee Lee · 2025
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MapAnything: Universal feed-forward metric 3d reconstruction
Nikhil Keetha, Norman Müller, Johannes Schönberger, Lorenzo Porzi, Yuchen Zhang, Tobias Fischer, Arno Knapitsch, Duncan Zauss, Ethan Weber, Nelson Antunes, et al · 2026
Closest in time.