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:

Prototype Refinement Network for Few-Shot Segmentation
Jinlu Liu, Yongqiang Qin
arXiv (Cornell University) (2020)
Open Access | Times Cited: 23

Showing 23 citing articles:

Learning What Not to Segment: A New Perspective on Few-Shot Segmentation
Chunbo Lang, Gong Cheng, Binfei Tu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 8047-8057
Open Access | Times Cited: 178
Base and Meta: A New Perspective on Few-Shot Segmentation
Chunbo Lang, Gong Cheng, Binfei Tu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Vol. 45, Iss. 9, pp. 10669-10686
Closed Access | Times Cited: 85
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
FECANet: Boosting Few-Shot Semantic Segmentation With Feature-Enhanced Context-Aware Network
Huafeng Liu, Pai Peng, Tao Chen, et al.
IEEE Transactions on Multimedia (2023) Vol. 25, pp. 8580-8592
Open Access | Times Cited: 47
A Location-Sensitive Local Prototype Network For Few-Shot Medical Image Segmentation
Qinji Yu, Kang Dang, Nima Tajbakhsh, et al.
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (2021)
Open Access | Times Cited: 35
ESDA: Zero-shot semantic segmentation based on an embedding semantic space distribution adjustment strategy
Jiaguang Li, Ying Wei, Wei Zhang, et al.
Image and Vision Computing (2025) Vol. 155, pp. 105456-105456
Closed Access
FGNet: Towards Filling the Intra-class and Inter-class Gaps for Few-shot Segmentation
Yuxuan Zhang, Wei Yang, Shaowei Wang
(2023), pp. 1749-1758
Open Access | Times Cited: 3
Cross Attention with Transformer for Few-shot Medical Image Segmentation
Yao Niu, Zhuoran Li, Shaozi Li
(2022), pp. 644-648
Closed Access | Times Cited: 3
Sam-Rsp: A New Few-Shot Segmentation Method Based on Segment Anything Model and Rough Segmentation Prompts
Jiaguang Li, Ying Wei, Wei Zhang, et al.
(2024)
Closed Access
Attentional adversarial training for few-shot medical image segmentation without annotations
Buhailiqiemu Awudong, Qi Li, Zili Liang, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0298227-e0298227
Open Access
Bi-orientated rectification few-shot segmentation network based on fine-grained prototypes
Aiping Yang, Zijia Sang, Yaran Zhou, et al.
Neurocomputing (2024), pp. 129160-129160
Closed Access
SAM-RSP: A new few-shot segmentation method based on segment anything model and rough segmentation prompts
Jiaguang Li, Ying Wei, Wei Zhang, et al.
Image and Vision Computing (2024) Vol. 150, pp. 105214-105214
Closed Access
On filling the intra-class and inter-class gaps for few-shot segmentation
Yuxuan Zhang, Shuchang Wang, Zhenbo Shi, et al.
Expert Systems with Applications (2024), pp. 125552-125552
Closed Access
Adaptive Local Prototype and Cycle Attention for Few-shot Medical Image Segmentation
Shenyang Qian, Maurice Pagnucco, Yang Song
(2023) Vol. 2, pp. 49-56
Closed Access | Times Cited: 1
Enhancing Few-Shot 3D Point Cloud Semantic Segmentation through Bidirectional Prototype Learning
Xuehang Guo, Hao Hu, Xiaoxi Yang, et al.
(2023), pp. 7-16
Closed Access | Times Cited: 1
SIL-LAND: Segmentation Incremental Learning in Aerial Imagery via LAbel Number Distribution Consistency
Junxi Li, Wenhui Diao, Xiaonan Lü, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-20
Closed Access | Times Cited: 2
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations
Shuo Lei, Xuchao Zhang, Jianfeng He, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 2
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
Cheng Ouyang, Carlo Biffi, Chen Chen, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 1
Few-Shot Semantic Segmentation via Prototype Augmentation with Image-Level Annotations
Shuo Lei, Xuchao Zhang, Jianfeng He, et al.
2022 IEEE International Conference on Multimedia and Expo (ICME) (2021), pp. 1-6
Closed Access | Times Cited: 1
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
Prune Truong, Martin Danelljan, Luc Van Gool, et al.
(2020)
Closed Access
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation
Qinji Yu, Kang Dang, Nima Tajbakhsh, et al.
arXiv (Cornell University) (2021)
Open Access
Prototypical Region Proposal Networks for Few-Shot Localization and Classification
Elliott Skomski, Aaron Tuor, Andrew Avila, et al.
arXiv (Cornell University) (2021)
Open Access
Target-aware for Few-shot Segmentation
Xiaoliu Luo, Taiping Zhang, Zhao Duan, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-8
Closed Access
Page 1

Scroll to top