Semih Günel

I am a Machine Learning Engineer at the Meta London office working on vision based Generative AI tools for Monetization. I am interested in computer vision, machine learning and self-supervised learning.

Previously, I graduated with my Ph.D. at EPFL, Lausanne, Switzerland in 2022. I did my Ph.D. in Computer Vision Lab under the supervision of Pascal Fua. My first author work was published in journals such as IJCV and Nature Methods, and workshops in NeurIPS, ICCV, and CVPR.

I obtained my B.Sc. in Computer Science at Bilkent University, Ankara, Turkey.

Email / Google Scholar / Linkedin / Twitter / Github

Main Publications

	Overcoming the Domain Gap in Contrastive Learning of Neural Action Representations Paper / Paper (Workshop) / Video / Code / Dataset / Bibtex Semih Günel, Florian Aymanns, Sina Honari, Pavan Ramdya, Pascal Fua IJCV, 2022 / NeurIPS Workshop, 2021 Self-supervised action recognition and domain adaptation on human and animal neural recordings using 3D markerless motion capture.
	LiftPose3D, a deep learning-based approach for transforming 2D to 3D pose in laboratory animals Paper / Video / Code / Dataset / Bibtex Adam Gostztolai, Semih Günel, Victor Lobato Rios, Marco Pietro Abrate, Daniel Morales, Helge Rhodin, Pascal Fua, Pavan Ramdya Nature Methods, 2021 / CVPR Workshop, 2021 Monocular 3D pose estimation on laboratory animals.
	Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals Paper / Poster / Video / Code / Dataset / Bibtex Siyuan Li, Semih Günel, Mirela Ostrek, Pavan Ramdya, Pascal Fua, Helge Rhodin CVPR, 2020 Unsupervised pose-estimation using rough animal models.
	DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila Paper / Video / Code / Dataset / Bibtex Semih Günel, Helge Rhodin, Daniel Morales, João Campagnolo, Pavan Ramdya, Pascal Fua eLife, 2019 Multi-view motion capture system for the model organism Drosophila Melonagaster. Includes a dataset with 1M images containing 38 landmark annotations. Mentioned In: Nature Quanta Magazine EPFL Reddit
	Gravity as a Reference for Estimating a Person's Height from Video Paper / Poster / Video / Dataset / Bibtex Didier Bieler, Semih Günel, Pascal Fua, Helge Rhodin ICCV, 2019 Unsupervised monocular scale estimation on videos using object free-fall motion.
	What Face and Body Shapes Tell Us About Height Paper / Poster / Dataset / Bibtex Semih Günel, Helge Rhodin, Pascal Fua ICCV Workshop, 2019 Monocular scale/height estimation using single images. Monocular human pose dataset with 1e6 images and 12,000 unique people with known height.
Vision Consultation
	Long-term imaging of the ventral nerve cord Paper / Code / Dataset / Bibtex Laura Hermans, Murat Kaynak, Jonas Braun, Victor Lobato Ríos, Chin-Lin Chen, Semih Günel, Florian Aymanns, Mahmut Selman Sakar, Pavan Ramdya Nature Communications, 2022 Long-term microscopy imaging of animal nervous system.
	Ascending neurons convey behavioral state to integrative sensory and action selection centers in the brain Paper / Video / Code / Dataset / Bibtex Chin-Lin Chen, Florian Aymanns, Ryo Minegishi, Victor D. V. Matsuda, Nicolas Talabot, Semih Günel, Barry J. Dickson, Pavan Ramdya Nature Neuroscience, 2023 Understanding the behavioral properties of neurons using two-photon recordings and motion capture.

JB's HTML template.