512 citations · 761 across the 20 of their papers we have counts for
4 papers · 1 filter
PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Peng Tang, Xinggang Wang, Song Bai +4
Weakly Supervised Object Detection (WSOD), using only image-level annotations to train object detectors, is of growing importance in object recognition. In this paper, we propose a…
Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound
Yan Wang, Yuyin Zhou, Peng Tang +3
Deep convolutional neural networks (CNNs), especially fully convolutional networks, have been widely applied to automatic medical image segmentation problems, e.g., multi-organ seg…
Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training
Yuyin Zhou, Yan Wang, Peng Tang +4
In multi-organ segmentation of abdominal CT scans, most existing fully supervised deep learning algorithms require lots of voxel-wise annotations, which are usually difficult, expe…
Object Detection in Videos by High Quality Object Linking
Peng Tang, Chunyu Wang, Xinggang Wang +3
Compared with object detection in static images, object detection in videos is more challenging due to degraded image qualities. An effective way to address this problem is to expl…