• School of Engineering and Applied Science, Aston University

    B4 7ET Birmingham

    United Kingdom

  • United Kingdom

20082019
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Personal profile

General

I am a Computer Vision researcher currently employed as a Senior Lecturer at Aston University in Birmingham, UK. Prior to that I was a Senior Research Scientist in Toshiba Research Laboratory in Cambridge, UK where I was a member of the Computer Vision Group while concurrently holding a Junior Research Fellowship in Wolfson College, Cambridge. Even earlier, I was a PhD student in in the Machine Intelligence Laboratory in the Department of EngineeringUniversity of Cambridge. Many years ago as an undergraduate I studied Mathematics and Computer Science at Imperial College, London.

Research Interests


My research interests broadly fall into the following four areas:

  • problems in the interface between Computer Vision and Graphics including Shape-from-X
  • video analysis and large scale content-based image retrieval
  • deep reinforcement learning and in particular the idea of transferring knowledge between agents and tasks
  • extracting joint semantic representations of images, video and text.

Qualifications

  • PhD in Computer Vision from Cambridge University Engineering Dept
  • MSci in Mathematics and Computer Science from Imperial College, London

Contact Details

Phone number: 0121 204 3452 
Email: g.vogiatzis@aston.ac.uk 
Room Number: MB211F

Fingerprint Dive into the research topics where George Vogiatzis is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 1 Similar Profiles
Reinforcement learning Engineering & Materials Science
Cameras Engineering & Materials Science
Photometric Stereo Mathematics
Semantics Engineering & Materials Science
Pixels Engineering & Materials Science
Facades Engineering & Materials Science
Intelligent agents Engineering & Materials Science
Recurrent neural networks Engineering & Materials Science

Research Output 2008 2019

A Deep Learning Approach to Automatic Caption Generation for News Images

Batra, V., He, Y. & Vogiatzis, G., 1 Jan 2019, The 11th International Conference on Language Resources and Evaluation (LREC).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
File
Recurrent neural networks
Network architecture
Internet
Deep neural networks
Deep learning

A Deep Reinforcement Learning Agent for Traffic Intersection Control Optimization

Garg, D., Chli, M. & Vogiatzis, G., Oct 2019.

Research output: Contribution to conferencePaper

Reinforcement learning
Traffic signals
Decision making
Cameras
Throughput

Domain Adaptation for Reinforcement Learning on the Atari

Carr, T., Chli, M. & Vogiatzis, G., 8 May 2019, Proceedings of the 2019 International Conference on Autonomous Agents and Multi-Agent Systems. ACM, p. 1859-1861

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
File
Reinforcement learning
Learning systems
Experiments

How to read paintings: Semantic art understanding with multi-modal retrieval

Garcia, N. & Vogiatzis, G., 29 Jan 2019, Computer Vision – ECCV 2018 Workshops, Proceedings. Roth, S. & Leal-Taixé, L. (eds.). Springer, Vol. 11130. p. 676-691 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11130 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Painting
Retrieval
Semantics
Museums
Image Inpainting

Learning Non-Metric Visual Similarity for Image Retrieval

Garcia, N. & Vogiatzis, G., 10 Feb 2019, In : Image and Vision Computing. 82, p. 18-25 8 p.

Research output: Contribution to journalArticle

File
Image retrieval
Neural networks
Pixels

Thesis

Holistic interpretation of visual data based on topology: semantic segmentation of architectural facades

Author: Fathalla, R., 2017

Supervisor: Vogiatzis, G. (Supervisor) & Nabney, I. T. (Supervisor)

Student thesis: Doctoral ThesisDoctor of Philosophy

File