Computer Vision
xUnit Spatial Activation Function for Image Denoising
This article provides an in-depth look at the CVPR 2018 paper titled "xUnit: Learning a Spatial Activation Function for Efficient Image Restoration" and its importance in the domain of image reconstruction.

Concurrent Spatial and Channel Squeeze & Excitation (scSE) Nets
In this article, we will take a look at the paper "Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks" which serves as a design update for the popular Squeeze-and-Excitation attention module.
Shuffle Attention for Deep Convolutional Neural Networks (SA-Net)
This article gives an in-depth summary of the ICASSP paper titled "SA-Net: Shuffle Attention for Deep Convolutional Neural Networks."
Style-based Recalibration Module (SRM) Channel Attention
In this post, we will cover a novel form of channel attention called the Style Recalibration Module (SRM), an extension of the popular TPAMI paper: Squeeze-and-Excitation Networks.
Global Context Networks (GCNet) Explained
In this post, we will discuss a form of attention mechanism in computer vision known as Global Context Networks, first published at ICCV Workshops 2019.