Anil Armagan

Research Associate at Imperial Computer Vision & Learning Lab,

Department of Electrical and Electronic Engineering,

Imperial College London, South Kensington,

London, SW7 2AZ, UK


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Bio Summary

I'm currently a research associate at the Imperial Computer Vision & Learning Lab, Imperial College London under the supervision of Dr. Tae-Kyun Kim. I obtained a PhD degree in Sep, 2018 from the Institute for Computer Graphics and Vision, TU Graz under the supervision of Prof. Vincent Lepetit. My research interests are Computer Vision and Machine Learning algorithms, more specifically 3D hand pose estimation and camera localization for urban environments. I received my M.Sc. and B.Sc. Degrees in 2014 and 2012 respectively, at Dep. of Computer Engineering, Bilkent University. During his M.Sc. he worked on Multimedia Event Detection in videos under supervision of Prof. Pinar Duygulu.


Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek, ..., Gregory Rogez, Vincent Lepetit, Tae-Kyun Kim European Conference on Computer Vision (ECCV), 2020.
Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects Juil Sock*, Pedro Castro*, Anil Armagan, Guillermo Garcia-Hernando and Tae-Kyun Kim. arXiv preprint arXiv:2003.12344, 2020
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction Pedro Castro, Anil Armagan and Tae-Kyun Kim. In Proc. of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.

Accurate Camera Registration in Urban Environments Using High-Level Feature Matching (bib) Anil Armagan, Martin Hirzer, Peter M. Roth and Vincent Lepetit, In Proc. British Machine Vision Conference (BMVC), 2017. Spotlight.
3D Localization in Urban Environments from Single Images (bib) Anil Armagan, Martin Hirzer, Peter M. Roth and Vincent Lepetit In Proc. Workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR), 2017. Oral.
Learning to Align Semantic Segmentation and 2.5D Maps for Geolocalization (bib) Anil Armagan, Martin Hirzer, Peter M. Roth and Vincent Lepetit In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017. Poster.
Semantic Segmentation for 3D Localization in Urban Environments (bib) Anil Armagan, Martin Hirzer and Vincent Lepetit In Proc., Joint Urban Remote Sensing Event (JURSE), 2017. Oral, Best Paper Award.

CMU Informedia@ Trecvid 2014: Semantic Indexing Lu Jiang, Xiaojun Chang, Zexi Mao, Anil Armagan, Zhengzhong Lan, Xuanchong Li, S Yu, Yi Yang, Deyu Meng, Pinar Duygulu-Sahin, Alexander Hauptmann. TRECVID, 2014.
Toward an estimation of user tagging credibility for social image retrieval Alexandru Lucian Ginsca, Adrian Popescu, Bogdan Ionescu, Anil Armagan, Ioannis Kanellos Proceedings of the 22nd ACM international conference on Multimedia, 1021-1024, 2014


MUCKE Participation at Retrieving Diverse Social Images Task of MediaEval 2013. Anil Armagan, Adrian Popescu, Pinar Duygulu MediaEval 1043
Scene classification with random forests and object and color distributions Ahmet İşcen, Eren Gölge, Anil Armağan, Pinar Duygulu Signal Processing and Communications Applications Conference (SIU), 2013