Qing En

Orcid: 0000-0003-0173-7437

According to our database1, Qing En authored at least 14 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2023
Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification.
CoRR, 2023

Efficient Low-Rank GNN Defense Against Structural Attacks.
Proceedings of the IEEE International Conference on Knowledge Graph, 2023

Exemplar-FreeSOLO: Enhancing Unsupervised Instance Segmentation with Exemplars.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Annotation by Clicks: A Point-Supervised Contrastive Variance Method for Medical Semantic Segmentation.
CoRR, 2022

TPSN: Transformer-based multi-Prototype Search Network for few-shot semantic segmentation.
Comput. Electr. Eng., 2022

Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Exemplar Learning for Medical Image Segmentation.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Joint Multisource Saliency and Exemplar Mechanism for Weakly Supervised Video Object Segmentation.
IEEE Trans. Image Process., 2021

Context-sensitive zero-shot semantic segmentation model based on meta-learning.
Neurocomputing, 2021

Multimodal Dance Generation Networks Based on Audio-Visual Analysis.
Int. J. Multim. Data Eng. Manag., 2021

TMD-FS: Improving Few-Shot Object Detection with Transformer Multi-modal Directing.
Proceedings of the Pattern Recognition and Computer Vision - 4th Chinese Conference, 2021

2019
Deep feature representation based on privileged knowledge transfer.
Pattern Recognit. Lett., 2019

Human-Like Delicate Region Erasing Strategy for Weakly Supervised Detection.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2016
Human action recognition based on discriminative supervoxels.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016


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