Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Revisiting Self-Supervised Visual Representation Learning
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 682

Showing 26-50 of 682 citing articles:

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Jihoon Tack, Sangwoo Mo, Jongheon Jeong, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 209
Ternary Adversarial Networks With Self-Supervision for Zero-Shot Cross-Modal Retrieval
Xing Xu, Huimin Lu, Jingkuan Song, et al.
IEEE Transactions on Cybernetics (2019) Vol. 50, Iss. 6, pp. 2400-2413
Closed Access | Times Cited: 204
Models Genesis
Zongwei Zhou, Vatsal Sodha, Jiaxuan Pang, et al.
Medical Image Analysis (2020) Vol. 67, pp. 101840-101840
Open Access | Times Cited: 203
Self-Supervised Pretraining of 3D Features on any Point-Cloud
Zaiwei Zhang, Rohit Girdhar, Armand Joulin, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021), pp. 10232-10243
Open Access | Times Cited: 197
VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples
Pan Tian, Yibing Song, Tianyu Yang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 192
Towards a general-purpose foundation model for computational pathology
Richard J. Chen, Tong Ding, Ming Lu, et al.
Nature Medicine (2024) Vol. 30, Iss. 3, pp. 850-862
Open Access | Times Cited: 191
Large Scale Adversarial Representation Learning
Jeff Donahue, Karen Simonyan
arXiv (Cornell University) (2019)
Open Access | Times Cited: 188
Self-labelling via simultaneous clustering and representation learning
Yuki M. Asano, Christian Rupprecht, Andrea Vedaldi
International Conference on Learning Representations (2020)
Closed Access | Times Cited: 181
Self-Supervised MultiModal Versatile Networks
Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 176
Online Deep Clustering for Unsupervised Representation Learning
Xiaohang Zhan, Jiahao Xie, Ziwei Liu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
Open Access | Times Cited: 175
A Survey on Semi-, Self- and Unsupervised Learning for Image Classification
Lars Schmarje, Monty Santarossa, Simon‐Martin Schröder, et al.
IEEE Access (2021) Vol. 9, pp. 82146-82168
Open Access | Times Cited: 174
Uncovering the structure of clinical EEG signals with self-supervised learning
Hubert Banville, Omar Chehab, Aapo Hyvärinen, et al.
Journal of Neural Engineering (2020) Vol. 18, Iss. 4, pp. 046020-046020
Open Access | Times Cited: 167
Deep Comprehensive Correlation Mining for Image Clustering
Jianlong Wu, Keyu Long, Fei Wang, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 8149-8158
Open Access | Times Cited: 165
S4L: Self-Supervised Semi-Supervised Learning
Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 164
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization
Shujun Wang, Lequan Yu, Caizi Li, et al.
Lecture notes in computer science (2020), pp. 159-176
Open Access | Times Cited: 160
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 157
How Well Do Self-Supervised Models Transfer?
Linus Ericsson, Henry Gouk, Timothy M. Hospedales
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 152
Self-Supervised Domain Adaptation for Computer Vision Tasks
Jiaolong Xu, Liang Xiao, Antonio M. López
IEEE Access (2019) Vol. 7, pp. 156694-156706
Open Access | Times Cited: 145
When Does Self-supervision Improve Few-Shot Learning?
Jong-Chyi Su, Subhransu Maji, Bharath Hariharan
Lecture notes in computer science (2020), pp. 645-666
Closed Access | Times Cited: 142
Review on self-supervised image recognition using deep neural networks
Kriti Ohri, Mukesh Kumar
Knowledge-Based Systems (2021) Vol. 224, pp. 107090-107090
Closed Access | Times Cited: 139
Self-supervised Pretraining of Visual Features in the Wild
Priya Goyal, Mathilde Caron, Benjamin Lefaudeux, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 126
A visual-language foundation model for computational pathology
Ming Lu, Bowen Chen, Drew F. K. Williamson, et al.
Nature Medicine (2024) Vol. 30, Iss. 3, pp. 863-874
Open Access | Times Cited: 119
Pseudo-Supervised Deep Subspace Clustering
Juncheng Lv, Zhao Kang, Xiao Lu, et al.
IEEE Transactions on Image Processing (2021) Vol. 30, pp. 5252-5263
Open Access | Times Cited: 114
An overview of deep learning methods for multimodal medical data mining
Fatemeh Behrad, Mohammad Saniee Abadeh
Expert Systems with Applications (2022) Vol. 200, pp. 117006-117006
Closed Access | Times Cited: 98
Survey on Self-Supervised Learning: Auxiliary Pretext Tasks and Contrastive Learning Methods in Imaging
Saleh Albelwi
Entropy (2022) Vol. 24, Iss. 4, pp. 551-551
Open Access | Times Cited: 93

Scroll to top