8 citations · 19 across the 6 of their papers we have counts for
6 papers
Domain Agnostic Image-to-image Translation using Low-Resolution Conditioning
Mohamed Abid, Arman Afrasiyabi, Ihsen Hedhli +2
Generally, image-to-image translation (i2i) methods aim at learning mappings across domains with the assumption that the images used for translation share content (e.g., pose) but…
Image-to-Image Translation with Low Resolution Conditioning
Mohamed Abderrahmen Abid, Ihsen Hedhli, Jean-François Lalonde +1
Most image-to-image translation methods focus on learning mappings across domains with the assumption that images share content (e.g., pose) but have their own domain-specific info…
A Generative Model for Hallucinating Diverse Versions of Super Resolution Images
Mohamed Abderrahmen Abid, Ihsen Hedhli, Christian Gagné
Traditionally, the main focus of image super-resolution techniques is on recovering the most likely high-quality images from low-quality images, using a one-to-one low- to high-res…
Learning of Image Dehazing Models for Segmentation Tasks
Sébastien de Blois, Ihsen Hedhli, Christian Gagné
To evaluate their performance, existing dehazing approaches generally rely on distance measures between the generated image and its corresponding ground truth. Despite its ability…
Accumulating Knowledge for Lifelong Online Learning
Changjian Shui, Ihsen Hedhli, Christian Gagné
Lifelong learning can be viewed as a continuous transfer learning procedure over consecutive tasks, where learning a given task depends on accumulated knowledge --- the so-called k…
Diversity regularization in deep ensembles
Changjian Shui, Azadeh Sadat Mozafari, Jonathan Marek +2
Calibrating the confidence of supervised learning models is important for a variety of contexts where the certainty over predictions should be reliable. However, it has been report…