J Gan, W Wang - Proceedings of the AAAI Conference on Artificial …, 2021 - ojs.aaai.org
Given limited handwriting scripts, humans can easily visualize (or imagine) what the handwritten words/texts would look like with other arbitrary textual contents. Moreover, a …
D Sun, T Ren, C Li, H Su, J Zhu - arXiv preprint arXiv:1712.06424, 2017 - arxiv.org
Automatically writing stylized Chinese characters is an attractive yet challenging task due to its wide applicabilities. In this paper, we propose a novel framework named Style-Aware …
We propose a novel transformer-based styled handwritten text image generation approach, HWT, that strives to learn both style-content entanglement as well as global and local style …
J Gan, W Wang, J Leng, X Gao - ACM Transactions on Graphics (TOG), 2022 - dl.acm.org
Humans remain far better than machines at learning, where humans require fewer examples to learn new concepts and can use those concepts in richer ways. Take handwriting as an …
Despite the latest transcription accuracies reached using deep neural network architectures, handwritten text recognition still remains a challenging problem, mainly because of the large …
V Pippi, S Cascianelli… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Generating synthetic images of handwritten text in a writer-specific style is a challenging task, especially in the case of unseen styles and new words, and even more when these …
Representing a space of handwriting stroke styles includes the challenge of representing both the style of each character and the overall style of the human writer. Existing VRNN …
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or single …
Calligraphy imitation (CI) from a handful of target handwriting samples is such a challenging task that most of the existing writing style analysis or handwriting generation methods do not …