Robert-Jan Bruintjes

PhD candidate with Jan van Gemert @ Computer Vision Lab, TU Delft

I study Deep Neural Networks for Computer Vision, like CNNs and Vision Transformers, and how they learn to do their job. Topics of choice include learned equivariance, position information and the inductive bias of the self-attention operation. I’ve also dabbled in implicit neural convolutional operators a bit.

Highlights

Recent

NeurIPS 2023 paper: Color Equivariant Convolutions

September 2023 Co-authored paper with colleagues at TU Delft.

ICCVW 2023 paper: Benchmarking action recognition

August 2023 Co-authored paper with BSc students at TU Delft.

TA and lecturer for Computer Vision course

June 2023 I was head TA and lecturer in the 2023 edition of CV by Deep Learning at TU Delft.

More updates

Featured Publications

Publication January 2022 ICLR 2022
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes

We provide a high bandwidth, alias-free convolutional kernel parameterization with learnable kernel size and constant parameter cost.
ArXiv Code Poster Slides
Publication April 2023 CVPRW 2023
What Affects Learned Equivariance in Deep Image Recognition Models?

What Affects Learned Equivariance in Deep Image Recognition Models?

We find evidence that learned equivariance in image recognition models correlates with accuracy, then we show how to increase said equivariance.
ArXiv Poster

Publications

Color Equivariant Convolutional Networks
NeurIPS 2023 Attila Lengyel, Ombretta Strafforello, Robert-Jan Bruintjes, Alexander Gielisse, Jan van Gemert
ArXiv Code
Benchmarking Data Efficiency and Computational Efficiency of Temporal Action Localization Models
ICCVW 2023 Jan Warchocki, Teodor Oprescu, Yunhan Wang, Alexandru Damacus, Paul Misterka, Robert-Jan Bruintjes, Attila Lengyel, Ombretta Strafforello, Jan van Gemert
ArXiv DOI
VIPriors 3: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
ArXiv Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios, Osman Semih Kayhan, Davide Zambrano, Nergis Tomen, Jan van Gemert
Website ArXiv Code DOI
What Affects Learned Equivariance in Deep Image Recognition Models?
CVPRW 2023 Robert-Jan Bruintjes*, Tomasz Motyka*, Jan van Gemert
ArXiv Poster
VIPriors 2: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
ArXiv Attila Lengyel, Robert-Jan Bruintjes, Marcos Baptista Rios, Osman Semih Kayhan, Davide Zambrano, Nergis Tomen, Jan van Gemert
Website ArXiv Code
See all publications

Contact

I am always willing to talk about collaboration or supervision. Please find my contact info at the top of the page.

Office

TU Delft, building 28, room 6.E.280
Van Mourik Broekmanweg 6
2628 XE Delft
The Netherlands