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Recent developments in monocular depth estimation methods enable high-quality depth estimation of single-view images but fail to estimate consistent video depth across different frames.
Recovering surface layout from an image
Derek Hoiem, Alexei A Efros, and Martial Hebert · 2007
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Sift flow: Dense correspondence across different scenes
Ce Liu, Jenny Yuen, Antonio Torralba, Josef Sivic, and William T Freeman · 2008
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A naturalistic open source movie for optical flow evaluation
Daniel J Butler, Jonas Wulff, Garrett B Stanley, and Michael J Black · 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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Virtual worlds as proxy for multi-object tracking analysis
Adrien Gaidon, Qiao Wang, Yohann Cabon, and Eleonora Vig · 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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A benchmark dataset and evaluation methodology for video object segmentation
Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, and Alexander Sorkine-Hornung · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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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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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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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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Consistent video depth estimation
Xuan Luo, Jia-Bin Huang, Richard Szeliski, Kevin Matzen, and Johannes Kopf · 2020
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
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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Adabins: Depth estimation using adaptive bins
Shariq Farooq Bhat, Ibraheem Alhashim, and Peter Wonka · 2021
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Robust consistent video depth estimation
Johannes Kopf, Xuejian Rong, and Jia-Bin Huang · 2021
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Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Zachary Teed and Jia Deng · 2021
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Transformer-based attention networks for continuous pixel-wise prediction
Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe, and Elisa Ricci · 2021
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Consistent depth of moving objects in video
Zhoutong Zhang, Forrester Cole, Richard Tucker, William T Freeman, and Tali Dekel · 2021
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Depth-aware generative adversarial network for talking head video generation
Fa-Ting Hong, Longhao Zhang, Li Shen, and Dan Xu · 2022
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P3depth: Monocular depth estimation with a piecewise planarity prior
Vaishakh Patil, Christos Sakaridis, Alexander Liniger, and Luc Van Gool · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Depth pro: Sharp monocular metric depth in less than a second
Aleksei Bochkovskii, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R Richter, and Vladlen Koltun · 2024
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Leap-vo: Long-term effective any point tracking for visual odometry
Weirong Chen, Le Chen, Rui Wang, and Marc Pollefeys · 2024
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Fine-tuning image-conditional diffusion models is easier than you think
Gonzalo Martin Garcia, Karim Abou Zeid, Christian Schmidt, Daan de Geus, Alexander Hermans, and Bastian Leibe · 2024
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Lotus: Diffusion-based visual foundation model for high-quality dense prediction
Jing He, Haodong Li, Wei Yin, Yixun Liang, Leheng Li, Kaiqiang Zhou, Hongbo Liu, Bingbing Liu, and Ying-Cong Chen · 2024
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Repurposing diffusion-based image generators for monocular depth estimation
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Less is more: Consistent video depth estimation with masked frames modeling
Yiran Wang, Zhiyu Pan, Xingyi Li, Zhiguo Cao, Ke Xian, and Jianming Zhang · 2022
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Neural window fully-connected crfs for monocular depth estimation
Weihao Yuan, Xiaodong Gu, Zuozhuo Dai, Siyu Zhu, and Ping Tan · 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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Zoedepth: Zero-shot transfer by combining relative and metric depth
Shariq Farooq Bhat, Reiner Birkl, Diana Wofk, Peter Wonka, and Matthias Müller · 2023
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Nope-nerf: Optimising neural radiance field with no pose prior
Wenjing Bian, Zirui Wang, Kejie Li, Jia-Wang Bian, and Victor Adrian Prisacariu · 2023
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Bingxin Ke, Anton Obukhov, Shengyu Huang, Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2024
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Mosca: Dynamic gaussian fusion from casual videos via 4d motion scaffolds
Jiahui Lei, Yijia Weng, Adam Harley, Leonidas Guibas, and Kostas Daniilidis · 2024
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Modgs: Dynamic gaussian splatting from causually-captured monocular videos
Qingming Liu, Yuan Liu, Jiepeng Wang, Xianqiang Lv, Peng Wang, Wenping Wang, and Junhui Hou · 2024
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Jiahao Lu, Jiacheng Deng, Ruijie Zhu, Yanzhe Liang, Wenfei Yang, Tianzhu Zhang, and Xu Zhou · 2024
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Unidepth: Universal monocular metric depth estimation
Luigi Piccinelli, Yung-Hsu Yang, Christos Sakaridis, Mattia Segu, Siyuan Li, Luc Van Gool, and Fisher Yu · 2024
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Learning temporally consistent video depth from video diffusion priors
Jiahao Shao, Yuanbo Yang, Hongyu Zhou, Youmin Zhang, Yujun Shen, Matteo Poggi, and Yiyi Liao · 2024
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Deep patch visual odometry
Zachary Teed, Lahav Lipson, and Jia Deng · 2024
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3d reconstruction with spatial memory
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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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Depthsplat: Connecting gaussian splatting and depth
Haofei Xu, Songyou Peng, Fangjinhua Wang, Hermann Blum, Daniel Barath, Andreas Geiger, and Marc Pollefeys · 2024
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No pose, no problem: Surprisingly simple 3d gaussian splats from sparse unposed images
Botao Ye, Sifei Liu, Haofei Xu, Xueting Li, Marc Pollefeys, Ming-Hsuan Yang, and Songyou Peng · 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
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Geowizard: Unleashing the diffusion priors for 3d geometry estimation from a single image
Xiao Fu, Wei Yin, Mu Hu, Kaixuan Wang, Yuexin Ma, Ping Tan, Shaojie Shen, Dahua Lin, and Xiaoxiao Long · 2025
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