1 citations · 1 across the 1 of their papers we have counts for
4 papers · 1 filter
Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images
Krishnakant Singh, Thanush Navaratnam, Jannik Holmer +2
A long-standing challenge in developing machine learning approaches has been the lack of high-quality labeled data. Recently, models trained with purely synthetic data, here termed…
Benchmarking Video Frame Interpolation
Simon Kiefhaber, Simon Niklaus, Feng Liu +1
Video frame interpolation, the task of synthesizing new frames in between two or more given ones, is becoming an increasingly popular research target. However, the current evaluati…
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods
Robin Hesse, Simone Schaub-Meyer, Stefan Roth
The field of explainable artificial intelligence (XAI) aims to uncover the inner workings of complex deep neural models. While being crucial for safety-critical domains, XAI inhere…
Content-Adaptive Downsampling in Convolutional Neural Networks
Robin Hesse, Simone Schaub-Meyer, Stefan Roth
Many convolutional neural networks (CNNs) rely on progressive downsampling of their feature maps to increase the network's receptive field and decrease computational cost. However,…