51 citations · 68 across the 4 of their papers we have counts for
10 papers
Handwriting Classification for the Analysis of Art-Historical Documents
Christian Bartz, Hendrik Rätz, Christoph Meinel
Digitized archives contain and preserve the knowledge of generations of scholars in millions of documents. The size of these archives calls for automatic analysis since a manual an…
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN
Christian Bartz, Joseph Bethge, Haojin Yang +1
Generative Adversarial Networks (GANs) have achieved state-of-the-art performance for several image generation and manipulation tasks. Different works have improved the limited und…
MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy?
Joseph Bethge, Christian Bartz, Haojin Yang +2
Binary Neural Networks (BNNs) are neural networks which use binary weights and activations instead of the typical 32-bit floating point values. They have reduced model sizes and al…
KISS: Keeping It Simple for Scene Text Recognition
Christian Bartz, Joseph Bethge, Haojin Yang +1
Over the past few years, several new methods for scene text recognition have been proposed. Most of these methods propose novel building blocks for neural networks. These novel bui…
LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks
Christian Bartz, Haojin Yang, Joseph Bethge +1
Recently, deep neural networks have achieved remarkable performance on the task of object detection and recognition. The reason for this success is mainly grounded in the availabil…
Learning to Train a Binary Neural Network
Joseph Bethge, Haojin Yang, Christian Bartz +1
Convolutional neural networks have achieved astonishing results in different application areas. Various methods which allow us to use these models on mobile and embedded devices ha…