Imperial College London

Alexandros Lattas

Faculty of EngineeringDepartment of Computing

Academic Visitor
 
 
 
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Contact

 

a.lattas Website

 
 
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Location

 

Huxley BuildingSouth Kensington Campus

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Summary

 

Summary

Alexandros Lattas is currently studying for a PhD in the Department of Computing at Imperial College London, supervised by Prof Stefanos Zafeiriou and Dr Abhijeet Ghosh. His research interests lie in the field of 3D Computer Vision, Machine Learning and Graphics, especially in capturing and generating photorealistic 3D humans.

He holds an MSc in Advanced Computing, by the Department of Computing, Imperial College London, a BSc in Management Science and Technology (Software Engineering Track) by the Athens Univerisy of Economics and Business. He also has been an affiliate student in the School of Management, University College London.

Alexandros is currently a part-time Researcher in Computer Vision at Huawei Technologies Co. Ltd. He has also worked as a Computer Vision Scientist at Facesoft Ltd., Research Associate in the Business Analytics Laboratory at AUEB and Tech Consultant Intern in Oracle.

Publications

Journals

Gitlina Y, Guarnera GC, Dhillon DS, et al., 2020, Practical measurement and reconstruction of spectral skin reflectance, Computer Graphics Forum: the International Journal of the Eurographics Association, Vol:39, ISSN:0167-7055, Pages:75-89

Gecer B, Lattas A, Ploumpis S, et al., 2020, Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks, Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol:12374 LNCS, ISSN:0302-9743, Pages:415-433

Tzirakis P, Papaioannou A, Lattas A, et al., 2020, Synthesising 3D Facial Motion from "In-the-Wild" Speech, 2020 15th Ieee International Conference on Automatic Face and Gesture Recognition (fg 2020), ISSN:2326-5396, Pages:265-272

Conference

Lattas A, Moschoglou S, Gecer B, et al., 2020, AvatarMe: Realistically Renderable 3D Facial Reconstruction “in-the-wild”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

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