DeepLabv2
DeepLabv2
**DeepLabv2** is an architecture for semantic segmentation that build on [DeepLab](https://paperswithcode.com/method/deeplab) with an atrous [spatial pyramid pooling](https://paperswithcode.com/method/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](https://paperswithcode.com/method/aspp) helps to account for different object sizes.
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
https://paperswithcode.com/paper/deeplab-semantic-image-segmentation-with-deep
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs