no code implementations • COLING 2022 • Jun Zhao, Xin Zhao, WenYu Zhan, Tao Gui, Qi Zhang, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu
To deal with this problem, this work proposes a cross-document semantic enhancement method, which consists of two modules: 1) To prevent distractions from irrelevant regions in the current document, we design a learnable attention mask mechanism, which is used to adaptively filter redundant information in the current document.
2 code implementations • ACL 2022 • Qin Liu, Rui Zheng, Bao Rong, Jingyi Liu, Zhihua Liu, Zhanzhan Cheng, Liang Qiao, Tao Gui, Qi Zhang, Xuanjing Huang
Adversarial robustness has attracted much attention recently, and the mainstream solution is adversarial training.
1 code implementation • 4 Feb 2024 • Liang Qiao, Jun Shi, Xiaoyu Hao, Xi Fang, Minfan Zhao, Ziqi Zhu, Junshi Chen, Hong An, Bing Li, Honghui Yuan, Xinyang Wang
Tensor program optimization on Deep Learning Accelerators (DLAs) is critical for efficient model deployment.
no code implementations • 17 Jan 2024 • Haowen Wang, Zhen Zhao, Zhao Jin, Zhengping Che, Liang Qiao, Yakun Huang, Zhipeng Fan, XIUQUAN QIAO, Jian Tang
Reconstructing real-world objects and estimating their movable joint structures are pivotal technologies within the field of robotics.
1 code implementation • ICCV 2023 • Longrong Yang, Xianpan Zhou, XueWei Li, Liang Qiao, Zheyang Li, Ziwei Yang, Gaoang Wang, Xi Li
Thus, the optimum of the distillation loss does not necessarily lead to the optimal student classification scores for dense object detectors.
1 code implementation • 4 Jul 2023 • Jun Shi, Hongyu Kan, Shulan Ruan, Ziqi Zhu, Minfan Zhao, Liang Qiao, Zhaohui Wang, Hong An, Xudong Xue
In this paper, we propose a hybrid densely connected network for tumor segmentation, named H-DenseFormer, which combines the representational power of the Convolutional Neural Network (CNN) and the Transformer structures.
no code implementations • 12 Jun 2023 • Jian Wang, Liang Qiao, Shichong Zhou, Jin Zhou, Jun Wang, Juncheng Li, Shihui Ying, Cai Chang, Jun Shi
To address this issue, a novel Two-Stage Detection and Diagnosis Network (TSDDNet) is proposed based on weakly supervised learning to enhance diagnostic accuracy of the ultrasound-based CAD for breast cancers.
1 code implementation • CVPR 2023 • Wei Su, Peihan Miao, Huanzhang Dou, Gaoang Wang, Liang Qiao, Zheyang Li, Xi Li
The active perception can take expressions as priors to extract relevant visual features, which can effectively alleviate the mismatches.
1 code implementation • 14 Jul 2022 • Ying Chen, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Xi Li
In this paper, to address this problem, we propose a novel cost-efficient Dynamic Low-resolution Distillation (DLD) text spotting framework, which aims to infer images in different small but recognizable resolutions and achieve a better balance between accuracy and efficiency.
Knowledge Distillation Optical Character Recognition (OCR) +1
1 code implementation • 14 Jul 2022 • Liang Qiao, Hui Jiang, Ying Chen, Can Li, Pengfei Li, Zaisheng Li, Baorui Zou, Dashan Guo, Yingda Xu, Yunlu Xu, Zhanzhan Cheng, Yi Niu
Compared with the previous opensource OCR toolbox, DavarOCR has relatively more complete support for the sub-tasks of the cutting-edge technology of document understanding.
2 code implementations • ACL 2022 • Xiao Wang, Shihan Dou, Limao Xiong, Yicheng Zou, Qi Zhang, Tao Gui, Liang Qiao, Zhanzhan Cheng, Xuanjing Huang
NER model has achieved promising performance on standard NER benchmarks.
Ranked #8 on Named Entity Recognition (NER) on WNUT 2017
no code implementations • 22 Mar 2022 • Eleanor Dunlop, Jette Jakobsen, Marie Bagge Jensen, Jayashree Arcot, Liang Qiao, Judy Cunningham, Lucinda J Black
MK-8 was found in Cheddar cheese only.
no code implementations • 21 Oct 2021 • Linlan Zhao, Dashan Guo, Yunlu Xu, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Xiangzhong Fang
Few-shot learning (FSL) aims to learn models that generalize to novel classes with limited training samples.
1 code implementation • 13 May 2021 • Liang Qiao, Zaisheng Li, Zhanzhan Cheng, Peng Zhang, ShiLiang Pu, Yi Niu, Wenqi Ren, Wenming Tan, Fei Wu
In this paper, we aim to obtain more reliable aligned bounding boxes by fully utilizing the visual information from both text regions in proposed local features and cell relations in global features.
Ranked #7 on Table Recognition on PubTabNet
1 code implementation • 13 May 2021 • Peng Zhang, Can Li, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Fei Wu
To address the above limitations, we propose a unified framework VSR for document layout analysis, combining vision, semantics and relations.
Ranked #3 on Document Layout Analysis on PubLayNet val
no code implementations • 24 Feb 2021 • Ying Wang, Liang Qiao, Chang Xu, Yepang Liu, Shing-Chi Cheung, Na Meng, Hai Yu, Zhiliang Zhu
The results showed that \textsc{Hero} achieved a high detection rate of 98. 5\% on a DM issue benchmark and found 2, 422 new DM issues in 2, 356 popular Golang projects.
Software Engineering
1 code implementation • 8 Dec 2020 • Liang Qiao, Ying Chen, Zhanzhan Cheng, Yunlu Xu, Yi Niu, ShiLiang Pu, Fei Wu
Recently end-to-end scene text spotting has become a popular research topic due to its advantages of global optimization and high maintainability in real applications.
Ranked #6 on Text Spotting on SCUT-CTW1500
1 code implementation • 27 May 2020 • Peng Zhang, Yunlu Xu, Zhanzhan Cheng, ShiLiang Pu, Jing Lu, Liang Qiao, Yi Niu, Fei Wu
Since real-world ubiquitous documents (e. g., invoices, tickets, resumes and leaflets) contain rich information, automatic document image understanding has become a hot topic.
1 code implementation • 17 Feb 2020 • Liang Qiao, Sanli Tang, Zhanzhan Cheng, Yunlu Xu, Yi Niu, ShiLiang Pu, Fei Wu
Many approaches have recently been proposed to detect irregular scene text and achieved promising results.
Ranked #8 on Text Spotting on SCUT-CTW1500
1 code implementation • 4 May 2019 • Yushu Chen, Hao Jing, Wenlai Zhao, Zhi-Qiang Liu, Ouyi Li, Liang Qiao, Wei Xue, Guangwen Yang
RSG is further combined with adaptive methods to construct ARSG for acceleration.