5 papers
Rethinking the Localization in Weakly Supervised Object Localization
Rui Xu, Yong Luo, Han Hu +3
Weakly supervised object localization (WSOL) is one of the most popular and challenging tasks in computer vision. This task is to localize the objects in the images given only the…
Unsupervised Cross-domain Pulmonary Nodule Detection without Source Data
Rui Xu, Yong Luo, Bo Du
Cross-domain pulmonary nodule detection suffers from performance degradation due to a large shift of data distributions between the source and target domain. Besides, considering t…
SGDA: Towards 3D Universal Pulmonary Nodule Detection via Slice Grouped Domain Attention
Rui Xu, Zhi Liu, Yong Luo +5
Lung cancer is the leading cause of cancer death worldwide. The best solution for lung cancer is to diagnose the pulmonary nodules in the early stage, which is usually accomplished…
LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection
Rui Xu, Yong Luo, Bo Du +2
Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based pulmonary nodule detectio…
Leveraging GAN Priors for Few-Shot Part Segmentation
Mengya Han, Heliang Zheng, Chaoyue Wang +3
Few-shot part segmentation aims to separate different parts of an object given only a few annotated samples. Due to the challenge of limited data, existing works mainly focus on le…