1 code implementation • 1 May 2024 • Zhiyu Fang, Shuai-Long Lei, Xiaobin Zhu, Chun Yang, Shi-Xue Zhang, Xu-Cheng Yin, Jingyan Qin
We then craft a mixed-context reasoning module based on the multi-layer perceptron (MLP) to learn the unified representations of inter-quadruples for ECE while accomplishing temporal knowledge reasoning.
no code implementations • 8 Jan 2024 • Shi-Xue Zhang, Chun Yang, Xiaobin Zhu, Hongyang Zhou, Hongfa Wang, Xu-Cheng Yin
Specifically, we propose an innovative reading-order estimation module (REM) that extracts reading-order information from the initial text boundary generated by an initial boundary module (IBM).
1 code implementation • ICCV 2023 • Hongyang Zhou, Xiaobin Zhu, Jianqing Zhu, Zheng Han, Shi-Xue Zhang, Jingyan Qin, Xu-Cheng Yin
Instead of assuming degradation are spatially invariant across the whole image, we learn correction filters to adjust degradations to known degradations in a spatially variant way by a novel linearly-assembled pixel degradation-adaptive regression module (DARM).
no code implementations • 5 Sep 2022 • Lei Chen, Haibo Qin, Shi-Xue Zhang, Chun Yang, XuCheng Yin
In this paper, we propose an efficient attention-free Single-Point Decoding Network (dubbed SPDN) for scene text recognition, which can replace the traditional attention-based decoding network.
1 code implementation • 26 Aug 2022 • Shi-Xue Zhang, Xiaobin Zhu, Lei Chen, Jie-Bo Hou, Xu-Cheng Yin
To be concrete, we adopt a Sigmoid Alpha Function (SAF) to transfer the distances between boundaries and their inside pixels to a probability map.
2 code implementations • 11 May 2022 • Shi-Xue Zhang, Chun Yang, Xiaobin Zhu, Xu-Cheng Yin
In our method, we explicitly model the text boundary via an innovative iterative boundary transformer in a coarse-to-fine manner.
no code implementations • 7 May 2022 • Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou, Xu-Cheng Yin
Then, we propose a graph-based fusion network via Graph Convolutional Network (GCN) to learn to reason and fuse the detection boxes for generating final instance boxes.
1 code implementation • 12 Mar 2022 • Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou, Chun Yang, Xu-Cheng Yin
In this paper, we propose an innovative Kernel Proposal Network (dubbed KPN) for arbitrary shape text detection.
1 code implementation • ICCV 2021 • Shi-Xue Zhang, Xiaobin Zhu, Chun Yang, Hongfa Wang, Xu-Cheng Yin
In this work, we propose a novel adaptive boundary proposal network for arbitrary shape text detection, which can learn to directly produce accurate boundary for arbitrary shape text without any post-processing.
2 code implementations • CVPR 2020 • Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou, Chang Liu, Chun Yang, Hongfa Wang, Xu-Cheng Yin
In this paper, we propose a novel unified relational reasoning graph network for arbitrary shape text detection.