no code implementations • 31 May 2023 • Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios, Osman Semih Kayhan, Davide Zambrano, Nergis Tomen, Jan van Gemert
The third edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" workshop featured four data-impaired challenges, focusing on addressing the limitations of data availability in training deep learning models for computer vision tasks.
1 code implementation • 5 May 2022 • Osman Semih Kayhan, Jan C. van Gemert
Which object detector is suitable for your context sensitive task?
no code implementations • 21 Jan 2022 • Attila Lengyel, Robert-Jan Bruintjes, Marcos Baptista Rios, Osman Semih Kayhan, Davide Zambrano, Nergis Tomen, Jan van Gemert
The second edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" challenges featured five data-impaired challenges, where models are trained from scratch on a reduced number of training samples for various key computer vision tasks.
1 code implementation • 4 Jun 2021 • Osman Semih Kayhan, Bart Vredebregt, Jan C. van Gemert
We show that object detectors can hallucinate and detect missing objects; potentially even accurately localized at their expected, but non-existing, position.
1 code implementation • 5 Mar 2021 • Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios, Osman Semih Kayhan, Jan van Gemert
We present the first edition of "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" challenges.
no code implementations • 26 Nov 2020 • Soroosh Poorgholi, Osman Semih Kayhan, Jan C. van Gemert
Video understanding has received more attention in the past few years due to the availability of several large-scale video datasets.
1 code implementation • 20 Oct 2020 • Rafal Pytel, Osman Semih Kayhan, Jan C. van Gemert
Occlusion degrades the performance of human pose estimation.
1 code implementation • CVPR 2020 • Osman Semih Kayhan, Jan C. van Gemert
In this paper we challenge the common assumption that convolutional layers in modern CNNs are translation invariant.