Yao Wei is a PhD candidate at Department of Earth Observation Science (EOS), Faculty ITC, University of Twente. Her research interests include computer vision and deep learning with specialization on 3D scene understanding.
Before, she worked in the fields of geo-information extraction from satellite images. She received the M.S. degree in photogrammetry and remote sensing from Wuhan University.
Expertise
Computer Science
- Generative Adversarial Networks
- Point Cloud
- Remote Sensing Image
- Surface Extraction
- Deep Learning
- Convolutional Neural Network
- Segmentation
Social Sciences
- Remote Sensing
Organisations
Publications
2023
BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models (2023)In IEEE/CVF International Conference on Computer Vision (ICCV) Workshops (pp. 2910-2919). IEEE. Wei, Y., Vosselman, G. & Yang, M. Y.
2022
Flow-based GAN for 3D Point Cloud Generation from a Single Image (2022)In 33rd British Machine Vision Conference 2022: London, UK, November 21-24, 2022. BMVA Press. Wei, Y., Vosselman, G. & Yang, M.https://bmvc2022.mpi-inf.mpg.de/569/Flow-based GAN for 3D point cloud generation from a single image (2022)[Working paper › Preprint]. ArXiv.org. Wei, Y., Vosselman, G. & Yang, M. Y.https://doi.org/10.48550/arXiv.2210.04072A combination of convolutional and graph neural networks for regularized road surface extraction (2022)IEEE transactions on geoscience and remote sensing, 60. Article 4409113. Yan, J., Ji, S. & Wei, Y.https://doi.org/10.1109/TGRS.2022.3151688Scribble-based weakly supervised deep learning for road surface extraction from remote sensing images (2022)IEEE transactions on geoscience and remote sensing, 60, 1-12. Article 9372390. Wei, Y. & Ji, S.https://doi.org/10.1109/TGRS.2021.3061213
2020
Simultaneous road surface and centerline extraction from large-scale remote sensing images using CNN-based segmentation and tracing (2020)IEEE transactions on geoscience and remote sensing, 58(12), 8919-8931. Article 9094008. Wei, Y., Zhang, K. & Ji, S.https://doi.org/10.1109/TGRS.2020.2991733
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