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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:

SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation
Siddhartha Gairola, Mayur Hemani, Ayush Chopra, et al.
(2020), pp. 573-579
Open Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
Gen Li, Varun Jampani, Laura Sevilla-Lara, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 306
Hypercorrelation Squeeze for Few-Shot Segmenation
Juhong Min, Dahyun Kang, Minsu Cho
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Closed Access | Times Cited: 181
Self-Guided and Cross-Guided Learning for Few-Shot Segmentation
Bingfeng Zhang, Jimin Xiao, Terry Qin
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), pp. 8308-8317
Open Access | Times Cited: 143
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Malik Boudiaf, Hoel Kervadec, Ziko Imtiaz Masud, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 139
Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation
Guo-Sen Xie, Jie Liu, Huan Xiong, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Closed Access | Times Cited: 122
Efficient and Explicit Modelling of Image Hierarchies for Image Restoration
Yawei Li, Yuchen Fan, Xiaoyu Xiang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 18278-18289
Open Access | Times Cited: 111
Self-support Few-Shot Semantic Segmentation
Qi Fan, Wenjie Pei, Yu‐Wing Tai, et al.
Lecture notes in computer science (2022), pp. 701-719
Open Access | Times Cited: 106
Generalized Few-shot Semantic Segmentation
Zhuotao Tian, Xin Lai, Li Jiang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
Open Access | Times Cited: 70
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation
Bohao Peng, Zhuotao Tian, Xiaoyang Wu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 23641-23651
Open Access | Times Cited: 55
Learning Meta-class Memory for Few-Shot Semantic Segmentation
Zhonghua Wu, Xiangxi Shi, Guosheng Lin, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021), pp. 497-506
Open Access | Times Cited: 101
Integrative Few-Shot Learning for Classification and Segmentation
Dahyun Kang, Minsu Cho
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
Open Access | Times Cited: 59
Hypercorrelation Squeeze for Few-Shot Segmentation
Juhong Min, Dahyun Kang, Minsu Cho
arXiv (Cornell University) (2021)
Open Access | Times Cited: 56
Few-Shot Segmentation via Divide-and-Conquer Proxies
Chunbo Lang, Gong Cheng, Binfei Tu, et al.
International Journal of Computer Vision (2023) Vol. 132, Iss. 1, pp. 261-283
Closed Access | Times Cited: 39
Few-Shot Semantic Segmentation with Cyclic Memory Network
Guo-Sen Xie, Huan Xiong, Jie Liu, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Closed Access | Times Cited: 54
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation
Binghao Liu, Yao Ding, Jianbin Jiao, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), pp. 9742-9751
Open Access | Times Cited: 40
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation
Jiacheng Chen, Bin-Bin Gao, Zongqing Lu, et al.
IEEE Transactions on Multimedia (2022) Vol. 25, pp. 4361-4373
Open Access | Times Cited: 23
Uncertainty-aware semi-supervised few shot segmentation
Soopil Kim, Philip Chikontwe, Sion An, et al.
Pattern Recognition (2023) Vol. 137, pp. 109292-109292
Open Access | Times Cited: 15
A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation
Qi Zhao, Binghao Liu, Shuchang Lyu, et al.
IEEE Transactions on Cognitive and Developmental Systems (2023) Vol. 16, Iss. 1, pp. 177-189
Open Access | Times Cited: 13
Prior Guided Feature Enrichment Network for Few-Shot Segmentation
Zhuotao Tian, Hengshuang Zhao, Michelle Shu, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 35
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation
Weide Liu, Zhonghua Wu, Yang Zhao, et al.
International Journal of Computer Vision (2023) Vol. 132, Iss. 4, pp. 1277-1291
Closed Access | Times Cited: 10
A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
Yuan‐Hao Lee, Fu-En Yang, Yu-Chiang Frank Wang
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2022), pp. 1607-1617
Closed Access | Times Cited: 14
MCEENet: Multi-Scale Context Enhancement and Edge-Assisted Network for Few-Shot Semantic Segmentation
Hongjie Zhou, Rufei Zhang, Xiaoyu He, et al.
Sensors (2023) Vol. 23, Iss. 6, pp. 2922-2922
Open Access | Times Cited: 8
MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation
Azade Farshad, Anastasia Makarevich, Vasileios Belagiannis, et al.
Lecture notes in computer science (2022), pp. 45-55
Closed Access | Times Cited: 13
Task-aware adaptive attention learning for few-shot semantic segmentation
Binjie Mao, Lingfeng Wang, Shiming Xiang, et al.
Neurocomputing (2022) Vol. 494, pp. 104-115
Closed Access | Times Cited: 13
Progressive One-shot Human Parsing
Haoyu He, Jing Zhang, Bhavani Thuraisingham, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 2, pp. 1522-1530
Open Access | Times Cited: 16
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