Wen Wu

Orcid: 0000-0003-0919-3948

Affiliations:
  • Hangzhou Dianzi University, Hangzhou, China


According to our database1, Wen Wu authored at least 15 papers between 2021 and 2024.

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Bibliography

2024
Annotate less but perform better: weakly supervised shadow detection via label augmentation.
Vis. Comput., October, 2024

Boosting Deep Unsupervised Edge Detection via Segment Anything Model.
IEEE Trans. Ind. Informatics, June, 2024

Omni-supervised shadow detection with vision foundation model.
J. Vis. Commun. Image Represent., 2024

2023
Don't worry about noisy labels in soft shadow detection.
Vis. Comput., December, 2023

How Many Annotations Do We Need for Generalizing New-Coming Shadow Images?
IEEE Trans. Circuits Syst. Video Technol., November, 2023

How to use extra training data for better edge detection?
Appl. Intell., September, 2023

Make Segment Anything Model Perfect on Shadow Detection.
IEEE Trans. Geosci. Remote. Sens., 2023

Exploring better target for shadow detection.
Knowl. Based Syst., 2023

2022
Learning to detect soft shadow from limited data.
Vis. Comput., 2022

Single-image shadow removal using detail extraction and illumination estimation.
Vis. Comput., 2022

Shadow detection via multi-scale feature fusion and unsupervised domain adaptation.
J. Vis. Commun. Image Represent., 2022

Single image shadow detection via uncertainty analysis and GCN-based refinement strategy.
J. Vis. Commun. Image Represent., 2022

Light-weight shadow detection via GCN-based annotation strategy and knowledge distillation.
Comput. Vis. Image Underst., 2022

Annotation is easy: Learning to generate a shadow mask.
Comput. Graph., 2022

2021
Shadow removal via dual module network and low error shadow dataset.
Comput. Graph., 2021


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