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Linkage Projects - Grant ID: LP140100221

Title
Linkage Projects - Grant ID: LP140100221
Funding
ARC | Linkage Projects
Contract (GA) number
LP140100221
Start Date
2014/01/01
End Date
2017/12/31
Open Access mandate
no
Organizations
-
More information
http://purl.org/au-research/grants/arc/LP140100221

 

  • Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition

    Gammulle, Harshala; Denman, Simon; Sridharan, Sridha; Fookes, Clinton (2017)
    Projects: ARC | Linkage Projects - Grant ID: LP140100221 (LP140100221)
    In this paper we address the problem of human action recognition from video sequences. Inspired by the exemplary results obtained via automatic feature learning and deep learning approaches in computer vision, we focus our attention towards learning salient spatial features via a convolutional neural network (CNN) and then map their temporal relationship with the aid of Long-Short-Term-Memory (LSTM) networks. Our contribution in this paper is a deep fusion framework that more effectively expl...

    Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks

    Fernando, Tharindu; Denman, Simon; Sridharan, Sridha; Fookes, Clinton (2018)
    Projects: ARC | Linkage Projects - Grant ID: LP140100221 (LP140100221)
    Visual saliency patterns are the result of a variety of factors aside from the image being parsed, however existing approaches have ignored these. To address this limitation, we propose a novel saliency estimation model which leverages the semantic modelling power of conditional generative adversarial networks together with memory architectures which capture the subject's behavioural patterns and task dependent factors. We make contributions aiming to bridge the gap between bottom-up feature ...
  • No project research data found
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