no code implementations • 7 Nov 2023 • Iman Abbasnejad, Fabio Zambetta, Flora Salim, Timothy Wiley, Jeffrey Chan, Russell Gallagher, Ehsan Abbasnejad
SCONE-GAN presents an end-to-end image translation, which is shown to be effective for learning to generate realistic and diverse scenery images.
1 code implementation • 4 Aug 2023 • Ravikiran Parameshwara, Ibrahim Radwan, Akshay Asthana, Iman Abbasnejad, Ramanathan Subramanian, Roland Goecke
Whilst deep learning techniques have achieved excellent emotion prediction, they still require large amounts of labelled training data, which are (a) onerous and tedious to compile, and (b) prone to errors and biases.
no code implementations • 12 Jun 2023 • Soujanya Narayana, Ibrahim Radwan, Ravikiran Parameshwara, Iman Abbasnejad, Akshay Asthana, Ramanathan Subramanian, Roland Goecke
Whilst a majority of affective computing research focuses on inferring emotions, examining mood or understanding the \textit{mood-emotion interplay} has received significantly less attention.
no code implementations • CVPR 2020 • Ehsan Abbasnejad, Iman Abbasnejad, Qi Wu, Javen Shi, Anton Van Den Hengel
For each potential action a distribution of the expected outcomes is calculated, and the value of the potential information gain assessed.
no code implementations • 25 May 2018 • Dung Nguyen, Kien Nguyen, Sridha Sridharan, Iman Abbasnejad, David Dean, Clinton Fookes
The use of deep learning techniques for automatic facial expression recognition has recently attracted great interest but developed models are still unable to generalize well due to the lack of large emotion datasets for deep learning.
no code implementations • 17 Jun 2017 • M. Ehsan Abbasnejad, Qinfeng Shi, Iman Abbasnejad, Anton Van Den Hengel, Anthony Dick
Traditional GANs use a deterministic generator function (typically a neural network) to transform a random noise input $z$ to a sample $\mathbf{x}$ that the discriminator seeks to distinguish.
no code implementations • 13 Jun 2017 • Iman Abbasnejad, Sridha Sridharan, Simon Denman, Clinton Fookes, Simon Lucey
In this paper the problem of complex event detection in the continuous domain (i. e. events with unknown starting and ending locations) is addressed.
no code implementations • 2 Aug 2016 • N. Dinesh Reddy, Iman Abbasnejad, Sheetal Reddy, Amit Kumar Mondal, Vindhya Devalla
Real time outdoor navigation in highly dynamic environments is an crucial problem.
no code implementations • 4 Sep 2015 • Iman Abbasnejad, Sridha Sridharan, Simon Denman, Clinton Fookes, Simon Lucey
A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence.