Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Di You

Di You

AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

Mar 18, 2022
Di You, Fenglin Liu, Shen Ge, Xiaoxia Xie, Jing Zhang, Xian Wu

Figure 1 for AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

Figure 2 for AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

Figure 3 for AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

Figure 4 for AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

* Accepted by MICCAI 2021 (the 24th International Conference on Medical Image Computing and Computer Assisted Intervention)

Access Paper or Ask Questions

COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

Jul 15, 2021
Di You, Jian Zhang, Jingfen Xie, Bin Chen, Siwei Ma

Figure 1 for COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

Figure 2 for COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

Figure 3 for COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

Figure 4 for COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

* IEEE Transactions on Image Processing, vol. 30, pp. 6066-6080, 2021
* Published in IEEE Transactions on Image Processing, 2021

Access Paper or Ask Questions

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

May 02, 2021
Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, Xiaoyu Zhang, Linjie Zhou, Sixin Lin, Ru Wang

Figure 1 for NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Figure 2 for NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Figure 3 for NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Figure 4 for NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

* Corrected the MOS values in Table 2

Access Paper or Ask Questions

ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

Mar 22, 2021
Di You, Jingfen Xie, Jian Zhang

Figure 1 for ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

Figure 2 for ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

Figure 3 for ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

Figure 4 for ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

* ICME 2021 ORAL accepted

Access Paper or Ask Questions

Bridging the Gap between Training and Inference for Neural Machine Translation

Jun 17, 2019
Wen Zhang, Yang Feng, Fandong Meng, Di You, Qun Liu

Figure 1 for Bridging the Gap between Training and Inference for Neural Machine Translation

Figure 2 for Bridging the Gap between Training and Inference for Neural Machine Translation

Figure 3 for Bridging the Gap between Training and Inference for Neural Machine Translation

Figure 4 for Bridging the Gap between Training and Inference for Neural Machine Translation

* 10 pages, 7 figures

Access Paper or Ask Questions