15 citations · 34 across the 12 of their papers we have counts for
12 papers
Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks
Rouzbeh Meshkinnejad, Jie Mei, Daniel Lizotte +1
Contrastive representation learning has emerged as a promising technique for continual learning as it can learn representations that are robust to catastrophic forgetting and gener…
Augment to Detect Anomalies with Continuous Labelling
Vahid Reza Khazaie, Anthony Wong, Yalda Mohsenzadeh
Anomaly detection is to recognize samples that differ in some respect from the training observations. These samples which do not conform to the distribution of normal data are call…
Anomaly Detection with Adversarially Learned Perturbations of Latent Space
Vahid Reza Khazaie, Anthony Wong, John Taylor Jewell +1
Anomaly detection is to identify samples that do not conform to the distribution of the normal data. Due to the unavailability of anomalous data, training a supervised deep neural…
Controlling Memorability of Face Images
Mohammad Younesi, Yalda Mohsenzadeh
Everyday, we are bombarded with many photographs of faces, whether on social media, television, or smartphones. From an evolutionary perspective, faces are intended to be remembere…
The Impact of Spatiotemporal Augmentations on Self-Supervised Audiovisual Representation Learning
Haider Al-Tahan, Yalda Mohsenzadeh
Contrastive learning of auditory and visual perception has been extremely successful when investigated individually. However, there are still major questions on how we could integr…
OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detection
John Taylor Jewell, Vahid Reza Khazaie, Yalda Mohsenzadeh
Novelty detection is the task of recognizing samples that do not belong to the distribution of the target class. During training, the novelty class is absent, preventing the use of…
CLAR: Contrastive Learning of Auditory Representations
Haider Al-Tahan, Yalda Mohsenzadeh
Learning rich visual representations using contrastive self-supervised learning has been extremely successful. However, it is still a major question whether we could use a similar…
Latent Vector Recovery of Audio GANs
Andrew Keyes, Nicky Bayat, Vahid Reza Khazaie +1
Advanced Generative Adversarial Networks (GANs) are remarkable in generating intelligible audio from a random latent vector. In this paper, we examine the task of recovering the la…
Multi Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face Recognition
Vahid Reza Khazaie, Nicky Bayat, Yalda Mohsenzadeh
State-of-the-art deep neural network models have reached near perfect face recognition accuracy rates on controlled high-resolution face images. However, their performance is drast…
Inverse mapping of face GANs
Nicky Bayat, Vahid Reza Khazaie, Yalda Mohsenzadeh
Generative adversarial networks (GANs) synthesize realistic images from a random latent vector. While many studies have explored various training configurations and architectures f…
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
Radoslaw Martin Cichy, Gemma Roig, Alex Andonian +6
In the last decade, artificial intelligence (AI) models inspired by the brain have made unprecedented progress in performing real-world perceptual tasks like object classification…
Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture
Erfan Zangeneh, Mohammad Rahmati, Yalda Mohsenzadeh
We propose a novel couple mappings method for low resolution face recognition using deep convolutional neural networks (DCNNs). The proposed architecture consists of two branches o…