publication . Other literature type . Conference object . Preprint . 2018

Learning Short-Cut Connections for Object Counting

Onoro-Rubio, D.; Niepert, M.; Roberto Lopez-Sastre;
Open Access
  • Published: 15 Nov 2018
  • Publisher: Zenodo
Abstract
Object counting is an important task in computer vision due to its growing demand in applications such as traffic monitoring or surveillance. In this paper, we consider object counting as a learning problem of a joint feature extraction and pixel-wise object density estimation with Convolutional-Deconvolutional networks. We introduce a novel counting model, named Gated U-Net (GU-Net). Specifically, we propose to enrich the U-Net architecture with the concept of learnable short-cut connections. Standard short-cut connections are connections between layers in deep neural networks which skip at least one intermediate layer. Instead of simply setting short-cut conne...
Subjects
free text keywords: Computer Science - Computer Vision and Pattern Recognition
Funded by
EC| 5GCITY
Project
5GCITY
5GCITY
  • Funder: European Commission (EC)
  • Project Code: 761508
  • Funding stream: H2020 | IA
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Other literature type . 2018
Provider: Datacite
Zenodo
Other literature type . 2018
Provider: Datacite
ZENODO
Conference object . 2018
Provider: ZENODO
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publication . Other literature type . Conference object . Preprint . 2018

Learning Short-Cut Connections for Object Counting

Onoro-Rubio, D.; Niepert, M.; Roberto Lopez-Sastre;