1 code implementation • Findings (ACL) 2022 • Yang Chi, Fausto Giunchiglia, Daqian Shi, Xiaolei Diao, Chuntao Li, Hao Xu
In addition, powered by the knowledge of radical systems in ZiNet, this paper introduces glyph similarity measurement between ancient Chinese characters, which could capture similar glyph pairs that are potentially related in origins or semantics.
no code implementations • 20 Apr 2024 • Xi Wang, Yichen Peng, Heng Fang, Haoran Xie, Xi Yang, Chuntao Li
Achieving this requires the effective decoupling of key attributes within the input image data, aiming to get representations accurately.
no code implementations • 14 Dec 2023 • Rixin Zhou, Ding Xia, Yi Zhang, Honglin Pang, Xi Yang, Chuntao Li
In this paper, we propose a learning-based image fragment pair-searching and -matching approach to solve the challenging restoration problem.
no code implementations • 1 Aug 2023 • Xiaolei Diao, Daqian Shi, Jian Li, Lida Shi, Mingzhe Yue, Ruihua Qi, Chuntao Li, Hao Xu
To increase the adaptability of ACCID, we propose a splicing-based synthetic character algorithm to augment the training samples and apply an image denoising method to improve the image quality.
1 code implementation • CVPR 2023 • Rixin Zhou, Jiafu Wei, Qian Zhang, Ruihua Qi, Xi Yang, Chuntao Li
The archaeological dating of bronze dings has played a critical role in the study of ancient Chinese history.
no code implementations • 8 Dec 2022 • Jiafu Wei, Ding Xia, Haoran Xie, Chia-Ming Chang, Chuntao Li, Xi Yang
We propose an interactive editing method that allows humans to help deep neural networks (DNNs) learn a latent space more consistent with human knowledge, thereby improving classification accuracy on indistinguishable ambiguous data.
1 code implementation • 16 Jul 2022 • Daqian Shi, Xiaolei Diao, Lida Shi, Hao Tang, Yang Chi, Chuntao Li, Hao Xu
Degraded images commonly exist in the general sources of character images, leading to unsatisfactory character recognition results.