Baris Gecer

Mr. Baris Gecer

Position:

Research Assistant / PhD Student

Email:

Personal website:

https://barisgecer.github.io/

Biography

Baris Gecer is a PhD. student in the Department of Computing, Imperial College London, under the supervision of Dr. Stefanos Zafeiriou, working as a member of iBUG group. 

His main research interests are photorealistic 3D Face modelling and synthesis by Generative Adversarial Nets and Deep Learning. Currently, He is doing researh internhip at Facebook Reality Labs

He obtained his M.S. degree from Bilkent University Computer Engineering department under the supervision of Prof. Selim Aksoy in 2016 and obtained his undergraduate degree in Computer Engineering from Hacettepe University in 2014. He also did an internship in Intelligent Systems Lab of the University of Groningen., with the supervision of Prof. Nicolai Petkov and Dr. George Azzopardi.

Publications

Journal articles

Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks

B. Gecer, S. Aksoy, E. Mercan, L. G. Shapiro, D. L. Weaver, J. G. Elmore. Pattern Recognition. 84: pp. 345 - 356, 2018.

Bibtex reference [hide]
@article{gecer2018breast,
    author = {B. Gecer and S. Aksoy and E. Mercan and L. G. Shapiro and D. L. Weaver and J. G. Elmore},
    pages = {345--356},
    journal = {Pattern Recognition},
    title = {Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks},
    url = {http://www.sciencedirect.com/science/article/pii/S0031320318302577},
    volume = {84},
    year = {2018},
}
Endnote reference [hide]

Color-blob-based COSFIRE filters for object recognition

B. Gecer, G. Azzopardi, N. Petkov. Image and Vision Computing. 57: pp. 165 - 174, 2017.

Bibtex reference [hide]
@article{gecer2017color,
    author = {B. Gecer and G. Azzopardi and N. Petkov},
    pages = {165--174},
    journal = {Image and Vision Computing},
    title = {Color-blob-based COSFIRE filters for object recognition},
    url = {http://www.sciencedirect.com/science/article/pii/S0262885616301895},
    volume = {57},
    year = {2017},
}
Endnote reference [hide]

Conference articles

GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

B. Gecer, S. Ploumpis, I. Kotsia, S. Zafeiriou. CVPR 2019. 2019.

Bibtex reference [hide]
@inproceedings{baris2019,
    author = {B. Gecer and S. Ploumpis and I. Kotsia and S. Zafeiriou},
    booktitle = {CVPR 2019},
    title = {GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction},
    year = {2019},
}
Endnote reference [hide]

Semi-supervised adversarial learning to generate photorealistic face images of new identities from 3D morphable model

B. Gecer, B. Bhattarai, J. Kittler, T. Kim. Proceedings of the European Conference on Computer Vision (ECCV). pp. 217 - 234, 2018.

Bibtex reference [hide]
@inproceedings{gecer2018semi,
    author = {B. Gecer and B. Bhattarai and J. Kittler and T. Kim},
    pages = {217--234},
    booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
    title = {Semi-supervised adversarial learning to generate photorealistic face images of new identities from 3D morphable model},
    year = {2018},
}
Endnote reference [hide]

Learning Deep Convolutional Embeddings for Face Representation Using Joint Sample- and Set-Based Supervision

B. Gecer, V. Balntas, T. Kim. The IEEE International Conference on Computer Vision (ICCV) Workshops. Oct 2017.

Bibtex reference [hide]
@inproceedings{Gecer_2017_ICCV,
    author = {B. Gecer and V. Balntas and T. Kim},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
    month = {Oct},
    title = {Learning Deep Convolutional Embeddings for Face Representation Using Joint Sample- and Set-Based Supervision},
    year = {2017},
}
Endnote reference [hide]