title: DMSANET: DUAL MULTI SCALE ATTENTION NETWORK
abstract: Attention mechanism of late has been quite popular in the computer vision community. A lot of work has been done to improve the performance of the network,
  although almost always it results in increased computational complexity. In this paper, we propose a new attention module that not only achieves the best performance
  but also has lesser parameters compared to most existing models. Our attention
  module can easily be integrated with other convolutional neural networks because
  of its lightweight nature. The proposed network named Dual Multi Scale Attention
  Network (DMSANet) is comprised of two parts: the first part is used to extract
  features at various scales and aggregate them, the second part uses spatial and
  channel attention modules in parallel to adaptively integrate local features with
  their global dependencies. We benchmark our network performance for Image
  Classification on ImageNet dataset, Object Detection and Instance Segmentation
  both on MS COCO dataset.
authors: Abhinav Sagar
hIndex: Abhinav Sagar 5