1 code implementation • 17 Nov 2023 • Xiaoqiong Xia, Chaoyu Zhu, Yuqi Shan, Fan Zhong, Lei Liu
Although many models have been developed to utilize the representations of drugs and cancer cell lines for predicting cancer drug responses (CDR), their performances can be improved by addressing issues such as insufficient data modality, suboptimal fusion algorithms, and poor generalizability for novel drugs or cell lines.
no code implementations • 14 Sep 2023 • Yang Li, Fan Zhong, Xin Wang, Shuangbing Song, Jiachen Li, Xueying Qin, Changhe Tu
The limitations of previous scoring methods and error metrics are analyzed, based on which we introduce our improved evaluation methods.
no code implementations • 13 Jul 2023 • Shuangbing Song, Fan Zhong, Tianju Wang, Xueying Qin, Changhe Tu
We demonstrate the advantages of our method for both interactive image editing and real-time high-resolution video processing.
1 code implementation • 26 Jul 2022 • Xuhui Tian, Xinran Lin, Fan Zhong, Xueying Qin
Optimization-based 3D object tracking is known to be precise and fast, but sensitive to large inter-frame displacements.
no code implementations • CVPR 2022 • Jiachen Li, Bin Wang, Shiqiang Zhu, Xin Cao, Fan Zhong, Wenxuan Chen, Te Li, Jason Gu, Xueying Qin
Our new benchmark dataset contains 20 textureless objects, 22 scenes, 404 video sequences and 126K images captured in real scenes.
no code implementations • 9 Dec 2021 • Ju Kang, Shijie Zhang, Yiyuan Niu, Fan Zhong, Xin Wang
Explaining biodiversity is a fundamental issue in ecology.
2 code implementations • 19 May 2018 • Jichao Zhang, Yezhi Shu, Songhua Xu, Gongze Cao, Fan Zhong, Meng Liu, Xueying Qin
To overcome such a key limitation, we propose Sparsely Grouped Generative Adversarial Networks (SG-GAN) as a novel approach that can translate images on sparsely grouped datasets where only a few samples for training are labelled.