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Hello! I am a computer vision and machine learning researcher. My goal is to build autonomous visual learners that can self-improve with minimal human intervention: How can we learn from uncurated and unlabeled data? I work at the Learning to Learn Lab, where I focus on self-supervision and continual learning. Before that, I obtained my PhD at the QUvA Lab , where I tackled visual detection using limited supervision, under the guidance of Arnold Smeulders. When I'm not researching, I love capturing beautiful cities with my GoPro. Tavira, Portugal, and Montreal, Canada, are among my favorite places. If you have any suggestions for my next adventure, feel free to contact me! Contact MeEmail | CV | Google Scholar | Twitter | LinkedIn |
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News
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11/2022
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Learning to Learn Lab, Eindhoven University of Technology, Netherlands
2022-2023
Post-doc Researcher |
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QUvA Deep Vision Lab, University of Amsterdam, Netherlands
2017-2022
PhD Researcher |
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Huawei Visual Search Lab, Helsinki, Finland
2021 March - 2022 January
Research Scientist Intern |
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Université Laval Computer Vision Lab, Quebec, Canada
2015 March - 2015 October
Research Intern |
Research
My research goal is to reduce the human supervision need of (continual) visual learners.
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Mert Kilickaya, Joost van de Weijer, Yuki Asano Preprint 2023 arXiv / Slides / Github We survey semi-, few-shot and self-supervised incremental learning. |
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Mert Kilickaya, Joaquin Vanschoren CVPRW 2023 (Oral) arXiv / Slides We introduce VINIL, a self-supervised incremental instance learner. |
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Mert Kilickaya, Arnold Smeulders BMVC 2021 arXiv / Slides We introduce Align-Former to detect human-object interactions from an image. |
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Mert Kilickaya, Arnold Smeulders WACV 2021 arXiv / Slides We introduce composition-aware learning to improve visual image search. |
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Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, Erkut Erdem EACL 2017 arXiv / Slides We propose Word-Mover Distance to evaluation image captioning. |
Patents
Visual Image Search via Conversational Interaction (Huawei)
Mert Kilickaya, Baiqiang XIA
US Patent, 2022, Link
Network for Interacted Object Localization (Qualcomm)
Mert Kilickaya, Arnold Smeulders
US Patent, 2022, Link
Subject-Object Interaction Recognition Model (Qualcomm)
Mert Kilickaya, Stratis Gavves, Arnold Smeulders
US Patent, 2022, Link
Context-driven Learning of Human-object Interactions (Qualcomm)
Mert Kilickaya, Noureldien Hussein, Stratis Gavves, Arnold Smeulders
US Patent, 2021, Link
Supervision
I am very fortunate to cross roads with the kind souls below.
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Fangqin Zhou (PhD, TU/e) | 2022- | Self-Supervised Learning for AI4Good |  |
Ran Piao (MSc, TU/e) | 2022- | Rapid ViT Architecture Search without Training |  |
Ceren Gok (PhD, TU/e) | 2022-2023 | Learning to Adapt for Continual Learning |  |
Kishan Parshotam (MSc, UvA) | 2020-2021 | Continual Learning of Object Instances |  |
Tarun Krishna (MSc, UvA) | 2019-2020 | Disentangling Rotation from Identity for Visual Instance Search |
Presentations
Here are some papers from other researchers that I have enjoyed studying and presenting. Congratulations to the authors on their awesome work!
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Source code credit to Dr. Jon Barron and ChatGPT |