Modern metrics for generative learning like Fréchet Inception Distance (FID) demonstrate impressive performance. However, they suffer from various shortcomings, like a bias towards specific generators and datasets. To address this problem, we propose the Fréchet...
Today’s generative neural networks allow the creation of high-quality synthetic speech at scale. While we welcome the creative use of this new technology, we must also recognize the risks. As synthetic speech is abused for monetary and identity theft, we require a...
The fast wavelet transform is an important workhorse in signal processing. Wavelets are local in the spatial- or temporal- and the frequency-domain. This property enables frequency domain analysis while preserving some spatiotemporal information. Until recently,...
The correct detection of article layout in historical newspaper pages remains challenging but is important for Natural Language Processing ( NLP) and machine learning applications in the field of digital history. Digital newspaper portals typically provide Optical...
Modeling long-term context in videos is crucial for many fine-grained tasks including temporal action segmentation. An interesting question that is still open is how much long-term temporal context is needed for optimal performance. While transformers can model the...
