no code implementations • 10 Nov 2021 • Zijian Gao, Jingyu Liu, Sheng Chen, Dedan Chang, Hao Zhang, Jinwei Yuan
Modern video-text retrieval frameworks basically consist of three parts: video encoder, text encoder and the similarity head.
Ranked #2 on
Video Retrieval
on MSR-VTT
(using extra training data)
no code implementations • 14 Oct 2021 • Zijian Gao, Huanyu Liu, Jingyu Liu
The current state-of-the-art methods for video corpus moment retrieval (VCMR) often use similarity-based feature alignment approach for the sake of convenience and speed.
1 code implementation • 11 Oct 2021 • Kaihao Zhang, Dongxu Li, Wenhan Luo, Jingyu Liu, Jiankang Deng, Wei Liu, Stefanos Zafeiriou
It is thus unclear how these algorithms perform on public face hallucination datasets.
1 code implementation • 21 Apr 2021 • Jie Lian, Jingyu Liu, Shu Zhang, Kai Gao, Xiaoqing Liu, Dingwen Zhang, Yizhou Yu
Leveraging on constant structure and disease relations extracted from domain knowledge, we propose a structure-aware relation network (SAR-Net) extending Mask R-CNN.
1 code implementation • 19 Oct 2020 • Jie Lian, Jingyu Liu, Yizhou Yu, Mengyuan Ding, Yaoci Lu, Yi Lu, Jie Cai, Deshou Lin, Miao Zhang, Zhe Wang, Kai He, Yijie Yu
The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab.
1 code implementation • 17 Jun 2020 • Jingyu Liu, Jie Lian, Yizhou Yu
Instance level detection of thoracic diseases or abnormalities are crucial for automatic diagnosis in chest X-ray images.
no code implementations • 6 Jan 2020 • Haleh Falakshahi, Victor M. Vergara, Jingyu Liu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah McEwen, Steven G. Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A. Turner, Sergey Plis, Vince D. Calhoun
Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality.
no code implementations • ICCV 2019 • Jingyu Liu, Gangming Zhao, Yu Fei, Ming Zhang, Yizhou Wang, Yizhou Yu
We show that the use of contrastive attention and alignment module allows the model to learn rich identification and localization information using only a small amount of location annotations, resulting in state-of-the-art performance in NIH chest X-ray dataset.
no code implementations • 12 Feb 2019 • Dongliang Xu, Bailing Wang, XiaoJiang Du, Xiaoyan Zhu, zhitao Guan, Xiaoyan Yu, Jingyu Liu
However, the advantages of convolutional neural networks depend on the data used by the training classifier, particularly the size of the training set.
no code implementations • ICCV 2017 • Jingyu Liu, Liang Wang, Ming-Hsuan Yang
In this paper, we explore the role of attributes by incorporating them into both referring expression generation and comprehension.