Similarity measures for time series are important problems for time seri...
In this work, we consider the typography generation task that aims at
pr...
A major approach for defending against adversarial attacks aims at
contr...
Scene text removal (STR) is the image transformation task to remove text...
There are various font styles in the world. Different styles give differ...
Ambigrams are graphical letter designs that can be read not only from th...
The scene text removal (STR) task aims to remove text regions and recove...
In documents and graphics, contours are a popular format to describe spe...
Semi-supervised domain adaptation is a technique to build a classifier f...
Disease severity regression by a convolutional neural network (CNN) for
...
This paper proposes a novel and efficient method for Learning from Label...
This work presents a novel self-supervised representation learning metho...
Automatic image-based disease severity estimation generally uses discret...
A multi-layer image is more valuable than a single-layer image from a gr...
Our goal is to generate fonts with specific impressions, by training a
g...
Signature verification, as a crucial practical documentation analysis ta...
In this paper, we propose an optimal rejection method for rejecting ambi...
This work presents a novel self-supervised pre-training method to learn
...
Different fonts have different impressions, such as elegant, scary, and ...
We propose TrueType Transformer (T3), which can perform character and fo...
Ulcerative colitis (UC) classification, which is an important task for
e...
Editing raster text is a promising but challenging task. We propose to a...
Fonts have had trends throughout their history, not only in when they we...
Book covers are intentionally designed and provide an introduction to a ...
When fonts are used on documents, they are intentionally selected by
des...
This paper analyzes a large number of logo images from the LLD-logo data...
Deep time series metric learning is challenging due to the difficult
tra...
We have specific impressions from the style of a typeface (font), sugges...
Various fonts give us various impressions, which are often represented b...
In convolutional neural network-based character recognition, pooling lay...
Oftentimes, patterns can be represented through different modalities. Fo...
The interpretability of neural networks (NNs) is a challenging but essen...
Temporal prediction is a still difficult task due to the chaotic behavio...
Analyzing the handwriting generation process is an important issue and h...
For visual object tracking, it is difficult to realize an almighty onlin...
In recent times, deep artificial neural networks have achieved many succ...
Our daily life is surrounded by textual information. Nowadays, the autom...
The purpose of this paper is to reveal the ability that Convolutional Ne...
We attempt to recognize and track lyric words in lyric videos. Lyric vid...
In convolutional neural networks (CNNs), pooling operations play importa...
Neural networks have become a powerful tool in pattern recognition and p...
In natural scenes and documents, we can find the correlation between a t...
In this paper, we tackle a challenging domain conversion task between ph...
There are a countless number of fonts with various shapes and styles. In...
Designing fonts requires a great deal of time and effort. It requires
pr...
In probabilistic classification, a discriminative model based on Gaussia...
Convolutional Neural Networks (CNN) have become state-of-the-art in the ...
In this paper, we conduct a large-scale study of font statistics in book...
This research attempts to construct a network that can convert online an...
In this paper, we propose a trainable multiplication layer (TML) for a n...