6 citations · 9 across the 7 of their papers we have counts for
9 papers
SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation
Iman Abbasnejad, Fabio Zambetta, Flora Salim +4
SCONE-GAN presents an end-to-end image translation, which is shown to be effective for learning to generate realistic and diverse scenery images. Most current image-to-image transl…
Efficient Labelling of Affective Video Datasets via Few-Shot & Multi-Task Contrastive Learning
Ravikiran Parameshwara, Ibrahim Radwan, Akshay Asthana +3
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…
A Weakly Supervised Approach to Emotion-change Prediction and Improved Mood Inference
Soujanya Narayana, Ibrahim Radwan, Ravikiran Parameshwara +4
Whilst a majority of affective computing research focuses on inferring emotions, examining mood or understanding the \textit{mood-emotion interplay} has received significantly less…
Gold Seeker: Information Gain from Policy Distributions for Goal-oriented Vision-and-Langauge Reasoning
Ehsan Abbasnejad, Iman Abbasnejad, Qi Wu +2
As Computer Vision moves from a passive analysis of pixels to active analysis of semantics, the breadth of information algorithms need to reason over has expanded significantly. On…
Meta Transfer Learning for Facial Emotion Recognition
Dung Nguyen, Kien Nguyen, Sridha Sridharan +3
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 t…
Bayesian Conditional Generative Adverserial Networks
M. Ehsan Abbasnejad, Qinfeng Shi, Iman Abbasnejad +2
Traditional GANs use a deterministic generator function (typically a neural network) to transform a random noise input to a sample that the discriminator seeks to…
Joint Max Margin and Semantic Features for Continuous Event Detection in Complex Scenes
Iman Abbasnejad, Sridha Sridharan, Simon Denman +2
In this paper the problem of complex event detection in the continuous domain (i.e. events with unknown starting and ending locations) is addressed. Existing event detection method…
Incremental Real-Time Multibody VSLAM with Trajectory Optimization Using Stereo Camera
N Dinesh Reddy, Iman Abbasnejad, Sheetal Reddy +2
Real time outdoor navigation in highly dynamic environments is an crucial problem. The recent literature on real time static SLAM don't scale up to dynamic outdoor environments. Mo…
Learning Temporal Alignment Uncertainty for Efficient Event Detection
Iman Abbasnejad, Sridha Sridharan, Simon Denman +2
In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and eff…