no code implementations • 25 Mar 2024 • Guangqian Yang, Kangrui Du, Zhihan Yang, Ye Du, Yongping Zheng, Shujun Wang
Our proposed framework is built on a masked Vim autoencoder to learn a unified multi-modal representation and long-dependencies contained in 3D medical images.
no code implementations • 1 Mar 2023 • Mingming Zhang, Ye Du, Zhenghui Hu, Qingjie Liu, Yunhong Wang
Extracting building footprints from remote sensing images has been attracting extensive attention recently.
1 code implementation • 15 Sep 2022 • Ye Du, Yujun Shen, Haochen Wang, Jingjing Fei, Wei Li, Liwei Wu, Rui Zhao, Zehua Fu, Qingjie Liu
Self-training has shown great potential in semi-supervised learning.
1 code implementation • CVPR 2022 • Ye Du, Zehua Fu, Qingjie Liu, Yunhong Wang
Moreover, armed with our method, we increase the segmentation mIoU of EPS from 70. 8% to 73. 6%, achieving new state-of-the-art.
Ranked #14 on Weakly-Supervised Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)
1 code implementation • 10 May 2021 • Ye Du, Zehua Fu, Qingjie Liu, Yunhong Wang
In this paper, we propose a transformer based approach for visual grounding.
1 code implementation • COLING 2020 • Yuanhang Ren, Ye Du
In this work, we propose a new retrofitting method called Heterogeneously Retrofitted Spectral Word Embedding.
no code implementations • 11 Sep 2020 • Jingchao Liu, Ye Du, Zehua Fu, Qingjie Liu, Yunhong Wang
Experiments on standard datasets shows our ARM can bring consistent improvements for both coarse annotations and fine annotations.
no code implementations • WS 2018 • Yuanhang Ren, Ye Du, Di Wang
Given a paragraph of an article and a corresponding query, instead of directly feeding the whole paragraph to the single BiDAF system, a sentence that most likely contains the answer to the query is first selected, which is done via a deep neural network based on TreeLSTM (Tai et al., 2015).