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Depth Anything has achieved remarkable success in monocular depth estimation with strong generalization ability.
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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Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 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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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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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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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Decoupled weight decay regularization
I Loshchilov · 2017
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A multi-view stereo benchmark with high-resolution images and multi-camera videos
Thomas Schops, Johannes L. Schonberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger · 2017
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Attention is all you need
A Vaswani · 2017
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Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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Fast depth densification for occlusion-aware augmented reality
Aleksander Holynski and Johannes Kopf · 2018
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Diode: A dense indoor and outdoor depth dataset
Vasiljevic Igor, Kolkin Nicholas, Shanyi Zhang, Ruotian Luo, Haochen Wang, FalconZ. Dai, AndreaF. Daniele, Mohammadreza Mostajabi, Steven Basart, MatthewR. Walter, and Gregory Shakhnarovich · 2019
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ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals
E. Palazzolo, J. Behley, P. Lottes, P. Giguère, and C. Stachniss · 2019
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Yohann Cabon, Naila Murray, and Martin Humenberger · 2020
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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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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
Cited alongside, same era.
Adabins: Depth estimation using adaptive bins
Shariq Farooq Bhat, Ibraheem Alhashim, and Peter Wonka · 2021
Cited alongside, same era.
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.
Irs: A large naturalistic indoor robotics stereo dataset to train deep models for disparity and surface normal estimation, 2021
Qiang Wang, Shizhen Zheng, Qingsong Yan, Fei Deng, Kaiyong Zhao, and Xiaowen Chu · 2021
Cited alongside, same era.
Consistent depth of moving objects in video
Zhoutong Zhang, Forrester Cole, Richard Tucker, William T Freeman, and Tali Dekel · 2021
Neural video depth stabilizer
Yiran Wang, Min Shi, Jiaqi Li, Zihao Huang, Zhiguo Cao, Jianming Zhang, Ke Xian, and Guosheng Lin · 2023
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Mamo: Leveraging memory and attention for monocular video depth estimation
Rajeev Yasarla, Hong Cai, Jisoo Jeong, Yunxiao Shi, Risheek Garrepalli, and Fatih Porikli · 2023
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Metric3d: Towards zero-shot metric 3d prediction from a single image
Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, and Chunhua Shen · 2023
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Controlvideo: Training-free controllable text-to-video generation
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang, Xiaopeng Zhang, Wangmeng Zuo, and Qi Tian · 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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Cited alongside, same era.
Towards real-time monocular depth estimation for robotics: A survey
Xingshuai Dong, Matthew A Garratt, Sreenatha G Anavatti, and Hussein A Abbass · 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.
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
Cited alongside, same era.
Gmflow: Learning optical flow via global matching
Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, and Dacheng Tao · 2022
Cited alongside, same era.
Neural window fully-connected crfs for monocular depth estimation
Weihao Yuan, Xiaodong Gu, Zuozhuo Dai, Siyu Zhu, and Ping Tan · 2022
Cited alongside, same era.
Zoedepth: Zero-shot transfer by combining relative and metric depth
Shariq Farooq Bhat, Reiner Birkl, Diana Wofk, Peter Wonka, and Matthias Müller · 2023
Cited alongside, same era.
Wenbo Hu, Xiangjun Gao, Xiaoyu Li, Sijie Zhao, Xiaodong Cun, Yong Zhang, Long Quan, and Ying Shan · 2024
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Wildavatar: Web-scale in-the-wild video dataset for 3d avatar creation
Zihao Huang, ShouKang Hu, Guangcong Wang, Tianqi Liu, Yuhang Zang, Zhiguo Cao, Wei Li, and Ziwei Liu · 2024
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Match-stereo-videos: Bidirectional alignment for consistent dynamic stereo matching
Junpeng Jing, Ye Mao, and Krystian Mikolajczyk · 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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Controlnext: Powerful and efficient control for image and video generation
Bohao Peng, Jian Wang, Yuechen Zhang, Wenbo Li, Ming-Chang Yang, and Jiaya Jia · 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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Moge: Unlocking accurate monocular geometry estimation for open-domain images with optimal training supervision, 2024
Ruicheng Wang, Sicheng Xu, Cassie Dai, Jianfeng Xiang, Yu Deng, Xin Tong, and Jiaolong Yang · 2024
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Depth any video with scalable synthetic data
Honghui Yang, Di Huang, Wei Yin, Chunhua Shen, Haifeng Liu, Xiaofei He, Binbin Lin, Wanli Ouyang, and Tong He · 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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Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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