53 citations · 294 across the 21 of their papers we have counts for
5 papers · 1 filter
Compositional Prototype Network with Multi-view Comparision for Few-Shot Point Cloud Semantic Segmentation
Xiaoyu Chen, Chi Zhang, Guosheng Lin +1
Point cloud segmentation is a fundamental visual understanding task in 3D vision. A fully supervised point cloud segmentation network often requires a large amount of data with poi…
Open Set Recognition with Conditional Probabilistic Generative Models
Xin Sun, Chi Zhang, Guosheng Lin +1
Deep neural networks have made breakthroughs in a wide range of visual understanding tasks. A typical challenge that hinders their real-world applications is that unknown samples m…
CRNet: Cross-Reference Networks for Few-Shot Segmentation
Weide Liu, Chi Zhang, Guosheng Lin +1
Over the past few years, state-of-the-art image segmentation algorithms are based on deep convolutional neural networks. To render a deep network with the ability to understand a c…
Conditional Gaussian Distribution Learning for Open Set Recognition
Xin Sun, Zhenning Yang, Chi Zhang +2
Deep neural networks have achieved state-of-the-art performance in a wide range of recognition/classification tasks. However, when applying deep learning to real-world applications…
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
Chi Zhang, Yujun Cai, Guosheng Lin +1
In this work, we develop methods for few-shot image classification from a new perspective of optimal matching between image regions. We employ the Earth Mover's Distance (EMD) as a…