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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:

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

Showing 26-50 of 139 citing articles:

Few-Shot Segmentation With Optimal Transport Matching and Message Flow
Weide Liu, Chi Zhang, Henghui Ding, et al.
IEEE Transactions on Multimedia (2022) Vol. 25, pp. 5130-5141
Open Access | Times Cited: 26
Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer
Wenjian Wang, Lijuan Duan, Yuxi Wang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 7055-7064
Closed Access | Times Cited: 25
Dual Contrastive Learning with Anatomical Auxiliary Supervision for Few-Shot Medical Image Segmentation
Huisi Wu, Fangyan Xiao, Chongxin Liang
Lecture notes in computer science (2022), pp. 417-434
Closed Access | Times Cited: 22
Doubly Deformable Aggregation of Covariance Matrices for Few-Shot Segmentation
Zhitong Xiong, Haopeng Li, Xiao Xiang Zhu
Lecture notes in computer science (2022), pp. 133-150
Closed Access | Times Cited: 22
Meta-Tuning Loss Functions and Data Augmentation for Few-Shot Object Detection
Berkan Demirel, Orhun Buğra Baran, Ramazan Gökberk Cinbiş
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 7339-7349
Open Access | Times Cited: 15
Prototype Comparison Convolutional Networks for One-Shot Segmentation
Lingbo Li, Zhichun Li, Fusen Guo, et al.
IEEE Access (2024) Vol. 12, pp. 54978-54990
Open Access | Times Cited: 5
APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation
Weizhao He, Yang Zhang, Wei Zhuo, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 33, pp. 23762-23772
Closed Access | Times Cited: 5
Efficient Sampling-based Gaussian Processes for few-shot semantic segmentation
Xinyi Zhang, Xiankai Lu, Yilong Yin, et al.
Pattern Recognition (2025), pp. 111542-111542
Closed Access
Dense Gaussian Processes for Few-Shot Segmentation
Joakim Johnander, Johan Edstedt, Michael Felsberg, et al.
Lecture notes in computer science (2022), pp. 217-234
Open Access | Times Cited: 19
Cross-Domain Few-Shot Semantic Segmentation
Shuo Lei, Xuchao Zhang, Jianfeng He, et al.
Lecture notes in computer science (2022), pp. 73-90
Closed Access | Times Cited: 19
A Strong Baseline for Generalized Few-Shot Semantic Segmentation
Sina Hajimiri, Malik Boudiaf, Ismail Ben Ayed, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023) Vol. 34, pp. 11269-11278
Open Access | Times Cited: 12
Dense affinity matching for Few-Shot Segmentation
Hao Chen, Yonghan Dong, Zhe‐Ming Lu, et al.
Neurocomputing (2024) Vol. 577, pp. 127348-127348
Open Access | Times Cited: 4
Prototype as query for few shot semantic segmentation
Leilei Cao, Yibo Guo, Ye Yuan, et al.
Complex & Intelligent Systems (2024) Vol. 10, Iss. 5, pp. 7265-7278
Open Access | Times Cited: 4
Addressing Background Context Bias in Few-Shot Segmentation Through Iterative Modulation
Lanyun Zhu, Tianrun Chen, Jianxiong Yin, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 35, pp. 3370-3379
Closed Access | Times Cited: 4
Adapt Before Comparison: A New Perspective on Cross-Domain Few-Shot Segmentation
Jonas Herzog
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 32, pp. 23605-23615
Closed Access | Times Cited: 4
PartSeg: Few-shot part segmentation via part-aware prompt learning
Mengya Han, Heliang Zheng, Chaoyue Wang, et al.
Pattern Recognition (2025), pp. 111326-111326
Open Access
Temporal Transductive Inference for Few-Shot Video Object Segmentation
Mennatullah Siam
International Journal of Computer Vision (2025)
Closed Access
Few-shot segmentation combined with domain adaptation: a flexible paradigm for parsing astronaut work environments
Qingwei Sun, Jiangang Chao, Wanhong Lin, et al.
Applied Intelligence (2025) Vol. 55, Iss. 7
Closed Access
Multi-scale prototype convolutional network for few-shot semantic segmentation
Xu Ding, Shun Yu, Jingxuan Zhou, et al.
PLoS ONE (2025) Vol. 20, Iss. 4, pp. e0319905-e0319905
Open Access
Efficient microstructure segmentation in three-dimensional imaging: Combining few-shot learning with the segment anything model
Po‐Yen Tung, Richard J. Harrison
Next Materials (2025) Vol. 8, pp. 100663-100663
Closed Access
CRCNet: Few-Shot Segmentation with Cross-Reference and Region–Global Conditional Networks
Weide Liu, Chi Zhang, Guosheng Lin, et al.
International Journal of Computer Vision (2022) Vol. 130, Iss. 12, pp. 3140-3157
Closed Access | Times Cited: 18
Interclass Prototype Relation for Few-Shot Segmentation
Atsuro Okazawa
Lecture notes in computer science (2022), pp. 362-378
Open Access | Times Cited: 17
Tackling background ambiguities in multi-class few-shot point cloud semantic segmentation
Lvlong Lai, Jian Chen, Chi Zhang, et al.
Knowledge-Based Systems (2022) Vol. 253, pp. 109508-109508
Closed Access | Times Cited: 16
Learning Foreground Information Bottleneck for few-shot semantic segmentation
Yutao Hu, Xin Huang, Xiaoyan Luo, et al.
Pattern Recognition (2023) Vol. 146, pp. 109993-109993
Closed Access | Times Cited: 10
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

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