no code implementations • 14 Aug 2023 • Xugong Qin, Pengyuan Lyu, Chengquan Zhang, Yu Zhou, Kun Yao, Peng Zhang, Hailun Lin, Weiping Wang
Different from existing methods which integrate multiple-granularity features or multiple outputs, we resort to the perspective of representation learning in which auxiliary tasks are utilized to enable the encoder to jointly learn robust features with the main task of per-pixel classification during optimization.
no code implementations • 10 May 2022 • Youhui Guo, Yu Zhou, Xugong Qin, Enze Xie, Weiping Wang
Recent scene text detection methods are almost based on deep learning and data-driven.
no code implementations • 8 Sep 2021 • Youhui Guo, Yu Zhou, Xugong Qin, Weiping Wang
In this paper, we propose a simple yet effective method for accurate arbitrary-shaped nearby scene text detection.
no code implementations • 8 Sep 2021 • Xugong Qin, Yu Zhou, Youhui Guo, Dayan Wu, Zhihong Tian, Ning Jiang, Hongbin Wang, Weiping Wang
We propose to use an MLP decoder instead of the "deconv-conv" decoder in the mask head, which alleviates the issue and promotes robustness significantly.
1 code implementation • 19 Oct 2020 • Zhi Qiao, Xugong Qin, Yu Zhou, Fei Yang, Weiping Wang
In this paper, we propose Gaussian Constrained Attention Network to deal with this problem.
no code implementations • 10 Jul 2020 • Xugong Qin, Yu Zhou, Dayan Wu, Yinliang Yue, Weiping Wang
Accurate detection of multi-oriented text with large variations of scales, orientations, and aspect ratios is of great significance.
no code implementations • 27 Aug 2019 • Xugong Qin, Yu Zhou, Dongbao Yang, Weiping Wang
The performance of the proposed method is comparable with the state-of-the-art methods with only 10% pixel-level annotated data and 90% rectangle-level weakly annotated data.