no code implementations • 23 Apr 2024 • Jingyang Lin, Yingda Xia, Jianpeng Zhang, Ke Yan, Le Lu, Jiebo Luo, Ling Zhang
In this paper, we extend the scope of Med-VLP to encompass 3D images, specifically targeting full-body scenarios, by using a multimodal dataset of CT images and reports.
1 code implementation • 29 Dec 2023 • Yunlong Tang, Jing Bi, Siting Xu, Luchuan Song, Susan Liang, Teng Wang, Daoan Zhang, Jie An, Jingyang Lin, Rongyi Zhu, Ali Vosoughi, Chao Huang, Zeliang Zhang, Feng Zheng, JianGuo Zhang, Ping Luo, Jiebo Luo, Chenliang Xu
With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly.
no code implementations • 28 Mar 2023 • Jingyang Lin, Junyu Chen, Hanjia Lyu, Igor Khodak, Divya Chhabra, Colby L Day Richardson, Irina Prelipcean, Andrew M Dylag, Jiebo Luo
In this work, we first analyze the correlations between three adverse neonatal outcomes and then formulate the diagnosis of multiple neonatal outcomes as a multi-task learning (MTL) problem.
1 code implementation • 21 Mar 2023 • Jingyang Lin, Hang Hua, Ming Chen, Yikang Li, Jenhao Hsiao, Chiuman Ho, Jiebo Luo
We propose a new joint video and text summarization task.
Ranked #1 on Video Summarization on videoxum
1 code implementation • 26 Sep 2022 • Jingyang Lin, Yu Wang, Qi Cai, Yingwei Pan, Ting Yao, Hongyang Chao, Tao Mei
Existing works attempt to solve the problem by explicitly imposing uncertainty on classifiers when OOD inputs are exposed to the classifier during training.
1 code implementation • NeurIPS 2021 • Yu Wang, Jingyang Lin, Jingjing Zou, Yingwei Pan, Ting Yao, Tao Mei
Our work reveals a structured shortcoming of the existing mainstream self-supervised learning methods.
1 code implementation • 14 Dec 2021 • Jingyang Lin, Yingwei Pan, Rongfeng Lai, Xuehang Yang, Hongyang Chao, Ting Yao
In this work, we quantitatively analyze the sub-text problem and present a simple yet effective design, COntrastive RElation (CORE) module, to mitigate that issue.
no code implementations • 5 Aug 2021 • Yu Wang, Jingyang Lin, Qi Cai, Yingwei Pan, Ting Yao, Hongyang Chao, Tao Mei
In this paper, we construct a novel probabilistic graphical model that effectively incorporates the low rank promoting prior into the framework of contrastive learning, referred to as LORAC.
no code implementations • 19 Oct 2018 • Jiafeng Xie, Bing Shuai, Jian-Fang Hu, Jingyang Lin, Wei-Shi Zheng
Recently, segmentation neural networks have been significantly improved by demonstrating very promising accuracies on public benchmarks.