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 • 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.
no code implementations • 26 Jul 2023 • Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao
Recent work in Machine Learning and Computer Vision has highlighted the presence of various types of systematic flaws inside ground truth object recognition benchmark datasets.
no code implementations • 18 Apr 2023 • Fausto Giunchiglia, Xiaolei Diao, Mayukh Bagchi
Data quality is critical for multimedia tasks, while various types of systematic flaws are found in image benchmark datasets, as discussed in recent work.
1 code implementation • CVPR 2023 • Jian Li, Ziyao Meng, Daqian Shi, Rui Song, Xiaolei Diao, Jingwen Wang, Hao Xu
Through representation learning, DNNs can map BFs into dense clusters in feature space, while the features of minority classes often show sparse clusters.
no code implementations • 13 Dec 2022 • Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao
We discuss two kinds of semantics relevant to Computer Vision (CV) systems - Visual Semantics and Lexical Semantics.
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.
no code implementations • 16 Jul 2022 • Daqian Shi, Xiaolei Diao, Hao Tang, Xiaomin Li, Hao Xing, Hao Xu
SENet aims to preserve the structural consistency of the character and normalize complex noise.
no code implementations • 12 Jul 2022 • Xiaolei Diao, Daqian Shi, Hao Tang, Qiang Shen, Yanzeng Li, Lei Wu, Hao Xu
The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets.
no code implementations • 26 Feb 2022 • Xiaolei Diao
To address this problem, we propose a novel unsupervised method to build visual semantics aware object hierarchy, aiming to get a classification model by learning from pure-visual information and to dissipate the bias of linguistic representations caused by SGP.
no code implementations • 17 Feb 2022 • Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao
Recent work in Machine Learning and Computer Vision has provided evidence of systematic design flaws in the development of major object recognition benchmark datasets.