Description
DeepLabv2 is an architecture for semantic segmentation that build on DeepLab with an atrous spatial pyramid pooling scheme. Here we have parallel dilated convolutions with different rates applied in the input feature map, which are then fused together. As objects of the same class can have different sizes in the image, ASPP helps to account for different object sizes.
Papers Using This Method
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation2024-04-02Threshold-adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation2022-08-23FDA: Fourier Domain Adaptation for Semantic Segmentation2020-04-11DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs2016-06-02