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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Unsupervised Monocular Depth Estimation with Left-Right Consistency
Clément Godard, Oisin Mac Aodha, Gabriel Brostow
(2017)
Open Access | Times Cited: 3020

Showing 1-25 of 3020 citing articles:

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, et al.
(2017), pp. 2242-2251
Open Access | Times Cited: 19113
Unsupervised Learning of Depth and Ego-Motion from Video
Tinghui Zhou, Matthew Brown, Noah Snavely, et al.
(2017), pp. 6612-6619
Open Access | Times Cited: 2548
Digging Into Self-Supervised Monocular Depth Estimation
Clément Godard, Oisin Mac Aodha, Michael Firman, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019)
Open Access | Times Cited: 1856
Deep Ordinal Regression Network for Monocular Depth Estimation
Huan Fu, Mingming Gong, Chaohui Wang, et al.
(2018), pp. 2002-2011
Open Access | Times Cited: 1697
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, et al.
arXiv (Cornell University) (2017)
Open Access | Times Cited: 1250
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
Zhichao Yin, Jianping Shi
(2018)
Open Access | Times Cited: 1181
Vision Transformers for Dense Prediction
René Ranftl, Alexey Bochkovskiy, Vladlen Koltun
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Open Access | Times Cited: 1152
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer
René Ranftl, Katrin Lasinger, David Hafner, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020) Vol. 44, Iss. 3, pp. 1623-1637
Open Access | Times Cited: 1058
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
Yan Wang, Wei‐Lun Chao, Divyansh Garg, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 983
SO-Net: Self-Organizing Network for Point Cloud Analysis
Jiaxin Li, Ben M. Chen, Gim Hee Lee
(2018), pp. 9397-9406
Open Access | Times Cited: 905
MegaDepth: Learning Single-View Depth Prediction from Internet Photos
Zhengqi Li, Noah Snavely
(2018), pp. 2041-2050
Open Access | Times Cited: 891
Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
Reza Mahjourian, Martin Wicke, Anelia Angelova
(2018)
Open Access | Times Cited: 778
Semi-Supervised Deep Learning for Monocular Depth Map Prediction
Yevhen Kuznietsov, Jörg Stückler, Bastian Leibe
(2017)
Open Access | Times Cited: 683
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction
Huangying Zhan, Ravi Garg, Chamara Saroj Weerasekera, et al.
(2018), pp. 340-349
Open Access | Times Cited: 668
Learning Depth from Monocular Videos Using Direct Methods
Chaoyang Wang, José M. Buenaposada, Rui Zhu, et al.
(2018), pp. 2022-2030
Open Access | Times Cited: 652
Stereo magnification
Tinghui Zhou, Richard Tucker, John P. Flynn, et al.
ACM Transactions on Graphics (2018) Vol. 37, Iss. 4, pp. 1-12
Open Access | Times Cited: 627
Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image
Fangchang Ma, Sertaç Karaman
(2018), pp. 4796-4803
Open Access | Times Cited: 605
Probabilistic Regression for Visual Tracking
Martin Danelljan, Luc Van Gool, Radu Timofte
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
Open Access | Times Cited: 585
3D Packing for Self-Supervised Monocular Depth Estimation
Vitor Guizilini, Rareş Ambruş, Sudeep Pillai, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 2482-2491
Open Access | Times Cited: 575
UnDeepVO: Monocular Visual Odometry Through Unsupervised Deep Learning
Ruihao Li, Sen Wang, Zhiqiang Long, et al.
(2018), pp. 7286-7291
Open Access | Times Cited: 538
Neural scene representation and rendering
S. M. Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, et al.
Science (2018) Vol. 360, Iss. 6394, pp. 1204-1210
Closed Access | Times Cited: 532
Multi-view Supervision for Single-View Reconstruction via Differentiable Ray Consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros, et al.
(2017)
Open Access | Times Cited: 531
DF-Net: Unsupervised Joint Learning of Depth and Flow Using Cross-Task Consistency
Yuliang Zou, Zelun Luo, Jia‐Bin Huang
Lecture notes in computer science (2018), pp. 38-55
Closed Access | Times Cited: 501
A General and Adaptive Robust Loss Function
Jonathan T. Barron
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 491
Cascade Residual Learning: A Two-Stage Convolutional Neural Network for Stereo Matching
Jiahao Pang, Wenxiu Sun, Jimmy Ren, et al.
(2017), pp. 878-886
Open Access | Times Cited: 476
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