no code implementations • 19 Nov 2020 • Yuanqiang Cai, Chang Liu, Weiqiang Wang, Qixiang Ye
With only bounding-box annotations in the spatial domain, existing video scene text detection (VSTD) benchmarks lack temporal relation of text instances among video frames, which hinders the development of video text-related applications.
3 code implementations • 9 Dec 2021 • Weijia Wu, Yuanqiang Cai, Debing Zhang, Sibo Wang, Zhuang Li, Jiahong Li, Yejun Tang, Hong Zhou
Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.
1 code implementation • 20 Mar 2022 • Weijia Wu, Yuanqiang Cai, Chunhua Shen, Debing Zhang, Ying Fu, Hong Zhou, Ping Luo
Recent video text spotting methods usually require the three-staged pipeline, i. e., detecting text in individual images, recognizing localized text, tracking text streams with post-processing to generate final results.
no code implementations • 4 Jul 2022 • Yuzhong Zhao, Yuanqiang Cai, Weijia Wu, Weiqiang Wang
Generally pre-training and long-time training computation are necessary for obtaining a good-performance text detector based on deep networks.
no code implementations • 11 Jul 2023 • Yongheng Zhang, Danfeng Yan, Yuanqiang Cai
In this paper, we introduce Uni-Removal, a twostage semi-supervised framework for addressing the removal of multiple degradations in real-world images using a unified model and parameters.