22 citations · 23 across the 4 of their papers we have counts for
4 papers
Dense Affinity Matching for Few-Shot Segmentation
Hao Chen, Yonghan Dong, Zheming Lu +4
Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to exploit the…
Multi-Content Interaction Network for Few-Shot Segmentation
Hao Chen, Yunlong Yu, Yonghan Dong +3
Few-Shot Segmentation (FSS) is challenging for limited support images and large intra-class appearance discrepancies. Most existing approaches focus on extracting high-level repres…
A Monkey Swing Counting Algorithm Based on Object Detection
Hao Chen, Zhe-Ming Lu, Jie Liu
This paper focuses on proposing a deep learning-based monkey swing counting algorithm. Nowadays, there are very few papers on monkey detection, and even fewer papers on monkey swin…
DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention
Zixuan Chen, Zewei He, Zhe-Ming Lu
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Some existing deep learning based methods are devoted to…