24 citations · 68 across the 9 of their papers we have counts for
5 papers · 2 filters
Point Cloud Instance Segmentation with Semi-supervised Bounding-Box Mining
Yongbin Liao, Hongyuan Zhu, Yanggang Zhang +3
Point cloud instance segmentation has achieved huge progress with the emergence of deep learning. However, these methods are usually data-hungry with expensive and time-consuming d…
Densely Semantic Enhancement for Domain Adaptive Region-free Detectors
Bo Zhang, Tao Chen, Bin Wang +3
Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled dat…
Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation
Yazhou Yao, Tao Chen, Guosen Xie +5
Semantic segmentation aims to classify every pixel of an input image. Considering the difficulty of acquiring dense labels, researchers have recently been resorting to weak labels…
EADNet: Efficient Asymmetric Dilated Network for Semantic Segmentation
Qihang Yang, Tao Chen, Jiayuan Fan +3
Due to real-time image semantic segmentation needs on power constrained edge devices, there has been an increasing desire to design lightweight semantic segmentation neural network…
Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation
Tao Chen, Guosen Xie, Yazhou Yao +4
One-shot semantic image segmentation aims to segment the object regions for the novel class with only one annotated image. Recent works adopt the episodic training strategy to mimi…