Multimodal Scene Understanding

He is Assistant Professor with 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. His research interests are in the fields of computer vision and photogrammetry with specialization on scene understanding, deep learning, UAV vision, and multi-sensor fusion. He published over 90 articles in international journals and conference proceedings. He serves as co-chair of ISPRS working group II/5 Dynamic Scene Analysis, and recipient of the ISPRS President's Honorary Citation (2016) and Best Science Paper Award at BMVC 2016. Since 2016, he is a Senior Member of IEEE. He is regularly serving as program committee member of conferences and reviewer for international journals. His works received several awards, including a DAGM-Prize 2002 , Dr.-Ing. Siegfried Werth Prize 2003, DAGM-Main Prize 2005, IVCNZ best student paper award , DAGM-Main Prize 2007, Olympus-Prize 2007, ICPRAM Best student paper award 2014, ICMC Best student paper award 2014, the WACV 2015 Challenge Award, the Günter Enderle Award (Eurographics) 2017 and the CVPR 2017 Multi-Object Tracking Challenge. In 2011, the European Commission awarded Bodo Rosenhahn with a 1.43 million Euros ERC-Starting Grant and in 2013 with a POC Grant. He published more than 180 research papers, journal articles and book chapters, holds more than 10 patents and edited several books. Full professor at the University of Verona, Italy, and director of the PAVIS (Pattern Analysis and Computer Vision) department at the Istituto Italiano di Tecnologia. He took the Laurea degree in Electronic Engineering in 1989 and a Ph.D. in Electronic Engineering and Computer Science in 1993 at the University of Genova, Italy.His main research interests include: computer vision and pattern recognition/machine learning, in particular, probabilistic techniques for image and video processing, with applications on video surveillance, biomedical image analysis and bioinformatics.

• 1. Introduction to Multimodal Scene UnderstandingMichael Ying Yang, Bodo Rosenhahn and Vittorio Murino2. Multi-modal Deep Learning for Multi-sensory Data FusionAsako Kanezaki, Ryohei Kuga, Yusuke Sugano and Yasuyuki Matsushita3. Multi-Modal Semantic Segmentation: Fusion of RGB and Depth Data in Convolutional Neural NetworksZoltan Koppanyi, Dorota Iwaszczuk, Bing Zha, Can Jozef Saul, Charles K. Toth and Alper Yilmaz4. Learning Convolutional Neural Networks for Object Detection with very little Training DataChristoph Reinders, Hanno Ackermann, Michael Ying Yang and Bodo Rosenhahn5. Multi-modal Fusion Architectures for Pedestrian DetectionDayan Guan, Jiangxin Yang, Yanlong Cao, Michael Ying Yang and Yanpeng Cao6. ThermalGAN: Multimodal Color-to-Thermal Image Translation for Person Re-Identification in Multispectral DatasetVladimir A. Knyaz and Vladimir V. Kniaz7. A Review and Quantitative Evaluation of Direct Visual-Inertia OdometryLukas von Stumberg, Vladyslav Usenko and Daniel Cremers8. Multimodal Localization for Embedded Systems: A SurveyImane Salhi, Martyna Poreba, Erwan Piriou, Valerie Gouet-Brunet and Maroun Ojail9. Self-Supervised Learning from Web Data for Multimodal RetrievalRaul Gomez, Lluis Gomez, Jaume Gibert and Dimosthenis Karatzas10. 3D Urban Scene Reconstruction and Interpretation from Multi-sensor ImageryHai Huang, Andreas Kuhn, Mario Michelini, Matthais Schmitz and Helmut Mayer11. Decision Fusion of Remote Sensing Data for Land Cover ClassificationArnaud Le Bris, Nesrine Chehata, Walid Ouerghemmi, Cyril Wendl, Clement Mallet, Tristan Postadjian and Anne Puissant12. Cross-modal learning by hallucinating missing modalities in RGB-D visionNuno Garcia, Pietro Morerio and Vittorio Murino