147 citations · 199 across the 9 of their papers we have counts for
5 papers · 1 filter
SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1
Capturing global contextual representations by exploiting long-range pixel-pixel dependencies has shown to improve semantic segmentation performance. However, how to do this effici…
The 1st Agriculture-Vision Challenge: Methods and Results
Mang Tik Chiu, Xingqian Xu, Kai Wang +39
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially f…
Self-Constructing Graph Convolutional Networks for Semantic Labeling
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1
Graph Neural Networks (GNNs) have received increasing attention in many fields. However, due to the lack of prior graphs, their use for semantic labeling has been limited. Here, we…
Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1
We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Co…
Dense Dilated Convolutions Merging Network for Land Cover Classification
Qinghui Liu, Michael Kampffmeyer, Robert Jessen +1
Land cover classification of remote sensing images is a challenging task due to limited amounts of annotated data, highly imbalanced classes, frequent incorrect pixel-level annotat…