77 citations · 96 across the 10 of their papers we have counts for
29 papers · 1 filter
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation
Liang Zeng, Attila Lengyel, Nergis Tömen +1
In this work, we leverage estimated depth to boost self-supervised contrastive learning for segmentation of urban scenes, where unlabeled videos are readily available for training…
Domain Adaptation for Rare Classes Augmented with Synthetic Samples
Tuhin Das, Robert-Jan Bruintjes, Attila Lengyel +2
To alleviate lower classification performance on rare classes in imbalanced datasets, a possible solution is to augment the underrepresented classes with synthetic samples. Domain…
Zero-Shot Day-Night Domain Adaptation with a Physics Prior
Attila Lengyel, Sourav Garg, Michael Milford +1
We explore the zero-shot setting for day-night domain adaptation. The traditional domain adaptation setting is to train on one domain and adapt to the target domain by exploiting u…
Exploiting Learned Symmetries in Group Equivariant Convolutions
Attila Lengyel, Jan C. van Gemert
Group Equivariant Convolutions (GConvs) enable convolutional neural networks to be equivariant to various transformation groups, but at an additional parameter and compute cost. We…
No frame left behind: Full Video Action Recognition
Xin Liu, Silvia L. Pintea, Fatemeh Karimi Nejadasl +2
Not all video frames are equally informative for recognizing an action. It is computationally infeasible to train deep networks on all video frames when actions develop over hundre…
Spectral Leakage and Rethinking the Kernel Size in CNNs
Nergis Tomen, Jan van Gemert
Convolutional layers in CNNs implement linear filters which decompose the input into different frequency bands. However, most modern architectures neglect standard principles of fi…