OTR: Synthesizing Overlay Text Dataset for Text Removal
Text removal is a crucial task in computer vision with applications such as privacy preservation, image editing, and media reuse. While existing research has primarily focused on …
Controllable Font Style for Visual Text Generation Using Reference Images
The rapid development of diffusion-based generative models has significantly advanced the field of text-to-image generation, enabling high-quality image creation for diverse …
Handwritten Text Generation with Character-specific Encoding for Style Imitation
We propose a novel method for handwritten text generation that uses a style encoder based on a vision transformer network. The style encoder encodes handwriting style from …
Meta Approach to Data Augmentation Optimization
Data augmentation policies drastically improve the performance of image recognition tasks, especially when the policies are optimized for the target data and tasks. In this paper, …
ryuichiro-hataya
JokerGAN: Memory-Efficient Model for Handwritten Text Generation with Text Line Awareness
Collecting labeled data for training of models for image recognition problems, including handwritten text recognition (HTR), is a tedious and expensive task. Recent work on …
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation
Data augmentation methods are indispensable heuristics to boost the performance of deep neural networks, especially in image recognition tasks. Recently, several studies have shown …
ryuichiro-hataya
Erasing Scene Text With Weak Supervision
Scene text erasing is a task of removing text from natural scene images, which has been gaining attention in recent years. The main motivation is to conceal private information …
Bag of Local Convolutional Triplets for Script Identification in Scene Text
The increasing interest in scene text reading in multilingual environments raises the need to recognize and distinguish between different writing systems. In this paper, we propose …