University of Twente
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Dr. habil. Y. Yang (Michael)

Universitair docent

Over mij

Michael Ying Yang is Assistant Professor in University of Twente, The Netherlands, heading a group working on scene understanding. 


He received the PhD degree (summa cum laude) from University of Bonn (Germany) in 2011. From 2008 to 2012, he worked as Researcher with the Department of Photogrammetry, University of Bonn, under supervision of Prof. Wolfgang Förstner. From 2012 to 2015, he was a Postdoctoral Researcher with the Institute for Information Processing, Leibniz University Hannover, under the supervision of Prof. Bodo Rosenhahn. From 2015 to 2016, he was a Senior Researcher with Computer Vision Lab Dresden, TU Dresden, collaborating with Prof. Carsten Rother. He received the venia legendi in Computer Science from Leibniz University Hannover in 06/2016.


His research interests are in the fields of computer vision with specialization on scene understanding. He works on Multimodal Learning and Deep Generative Models in the recent years. He published over 100 articles in international journals and conference proceedings and co-supervise 5 PhD students. He serves as Associate Editor of ISPRS Journal of Photogrammetry and Remote Sensing, and recipient of the ISPRS President's Honorary Citation (2016) and Best Science Paper Award at BMVC 2016. He co-organized 12 workshops with CVPR/ICCV/ECCV, and is guest editor of 4 journal special issues. Since 2016, he is a Senior Member of IEEE. He is regularly serving as program committee member of conferences and reviewer for international journals.

 

Please visit personal homepage for up-to-date details:

https://sites.google.com/site/michaelyingyang/

Expertises

Engineering & Materials Science
# Convolutional Neural Networks
# Deep Learning
# Image Classification
# Object Detection
# Semantics
# Unmanned Aerial Vehicles (Uav)
Earth & Environmental Sciences
# Segmentation
Physics & Astronomy
# Semantics

Verbonden aan

Onderzoek

His research is in the fields of Artificial intelligence (AI),  Computer Vision with specialization on Deep Learning, Graphical Models, Scene Understanding, Deep Generative Models, and Multimodal Learning.

Publicaties

Recent
Zeng, Y., Alidoost, F., Schilperoort, B., Liu, Y., Grootes, M. W., Wang, Y. , Song, Z. , Yu, D., Tang, E. , Han, Q. , van der Tol, C. , Zurita-Milla, R. , Yang, M. Y. , Girgin, S., Dzigan, Y. , & Su, Z. (2023). Towards an open digital twin of soil-plant system following Open Science . Abstract from EGU General Assembly 2023, Vienna, Austria. https://doi.org/10.5194/egusphere-egu23-9786
Wei, Y. , Vosselman, G. , & Yang, M. (2022). Flow-based GAN for 3D Point Cloud Generation from a Single Image. In 33rd British Machine Vision Conference 2022: London, UK, November 21-24, 2022 BMVA Press. https://bmvc2022.mpi-inf.mpg.de/569/
Lin, Y. (2022). Deep learning for semantic segmentation of airborne laser scanning point clouds. [PhD Thesis - Research UT, graduation UT, Faculty of Geo-Information Science and Earth Observation, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036554107
Liao, W., Hu, K. , Yang, M. Y., & Rosenhahn, B. (2022). Text to Image Generation with Semantic-Spatial Aware GAN. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 18166-18175). IEEE. https://doi.org/10.1109/CVPR52688.2022.01765
Fu, G., Jia, S., Zhu, W., Yang, J., Cao, Y. , Yang, M. Y., & Cao, Y. (2022). Fusion of multi-light source illuminated images for effective defect inspection on highly reflective surfaces. Mechanical systems and signal processing, 175, 1-13. [109109]. https://doi.org/10.1016/j.ymssp.2022.109109
He, S., Liao, W. , Yang, M. Y., Song, Y., Rosenhahn, B., & Xiang, T. (2022). Disentangled lifespan face synthesis. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 3857-3866). IEEE. https://doi.org/10.1109/ICCV48922.2021.00385
Cong, Y., Liao, W., Ackermann, H., Rosenhahn, B. , & Yang, M. Y. (2022). Spatial-temporal transformer for dynamic scene graph generation. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 16352-16362). IEEE. https://doi.org/10.1109/ICCV48922.2021.01606
Ding, J., Xue, N., Xia, G. S., Bai, X., Yang, W. , Yang, M., Belongie, S., Luo, J., Datcu, M., Pelillo, M., & Zhang, L. (2022). Object detection in aerial images: A large-scale benchmark and challenges. IEEE transactions on pattern analysis and machine intelligence, 44(11), 7778-7796. https://doi.org/10.1109/TPAMI.2021.3117983
Zhang, Z. (2022). Photogrammetric point clouds: quality assessment, filtering, and change detection. [PhD Thesis - Research UT, graduation UT, Faculty of Geo-Information Science and Earth Observation, University of Twente]. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). https://doi.org/10.3990/1.9789036552653
Xia, G. S., Ding, J., Qian, M., Xue, N., Han, J., Bai, X. , Yang, M. Y., Li, S., Belongie, S., Luo, J., Datcu, M., Pelillo, M., Zhang, L., Zhou, Q., Yu, C. H., Hu, K., Bu, Y., Tan, W., Yang, Z., ... Liu, F. (2021). LUAI challenge 2021 on learning to understand aerial images. In Proceedings - 2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021 (pp. 762-768). (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2021-October). IEEE. https://doi.org/10.1109/ICCVW54120.2021.00090
Kluger, F., Ackermann, H., Brachmann, E. , Yang, M. Y., & Rosenhahn, B. (2021). Cuboids revisited: learning robust 3D shape fitting to single RGB images. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 13065-13074). IEEE. https://doi.org/10.1109/CVPR46437.2021.01287
He, S., Liao, W. , Yang, M. Y., Yang, Y., Song, Y., Rosenhahn, B., & Xiang, T. (2021). Context-aware layout to image generation with enhanced object appearance. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 15044-15053). IEEE. https://doi.org/10.1109/CVPR46437.2021.01480
Cheng, H., Liao, W., Tang, X. , Yang, M. Y., Sester, M., & Rosenhahn, B. (2021). Exploring dynamic context for multi-path trajectory prediction. In 2021 IEEE International Conference on Robotics and Automation (ICRA) (pp. 12795-12801). IEEE. https://doi.org/10.1109/ICRA48506.2021.9562034
Kumaar, S. , Lyu, Y. , Nex, F. , & Yang, M. Y. (2021). CABiNet: Efficient Context Aggregation Network for Low-Latency Semantic Segmentation. In 2021 IEEE International Conference on Robotics and Automation (ICRA) (pp. 13517-13524). (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2021-May). IEEE. https://doi.org/10.1109/ICRA48506.2021.9560977
Liao, W., Lan, C. , Yang, M. Y., Zeng, W., & Rosenhahn, B. (2021). Target-tailored source-transformation for scene graph generation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 1663-1671). IEEE. https://doi.org/10.1109/CVPRW53098.2021.00182
Lyu, Y. (2021). Dynamic scene understanding using deep neural networks. [PhD Thesis - Research UT, graduation UT, Faculty of Geo-Information Science and Earth Observation, University of Twente]. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). https://doi.org/10.3990/1.9789036552233

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Naar mijn profiel

Onderwijs

Main educational responsibilities are teaching topics on deep learning, scene understanding with UAVs, image processing, 3D modeling and photogrammetry.

Verbonden aan Opleidingen

Master

Vakken Collegejaar  2022/2023

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
 

Vakken Collegejaar  2021/2022

Projecten

• EU project VeVuSafety 2022-2024

Artificial Intelligence for Traffic Safety between Vehicles and Vulnerable Road Users

Funded by EU, PI

• NWO eScience project 2021-2024
EcoExtreML: Accelerating Process Understanding for Ecosystem Functioning under Extreme Climates with Physics-Aware Machine Learning

Funded by The Netherlands eScience Center, co-PI

• DFG project 2017-2020-2023

Comprehensive Conjoint GPS and Video Data Analysis for Smart Maps

Funded by the German Research Foundation, co-PI

• DFG project 2015-2018

Holistic Scene Understanding

Funded by the German Research Foundation, PI

Contactgegevens

 
 

Bezoekadres

Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds (gebouwnr. 19), kamer 1308
Hallenweg 8
7522NH  Enschede

Postadres

Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds  1308
Postbus 217
7500 AE Enschede

Verbonden aan

Overige contactinformatie

https://research.utwente.nl/en/persons/michael-ying-yang
Universiteit Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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