501 citations · 530 across the 6 of their papers we have counts for
9 papers
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
Junlin Han, Mehrdad Shoeiby, Tim Malthus +7
Underwater image restoration is of significant importance in unveiling the underwater world. Numerous techniques and algorithms have been developed in the past decades. However, du…
Dual Contrastive Learning for Unsupervised Image-to-Image Translation
Junlin Han, Mehrdad Shoeiby, Lars Petersson +1
Unsupervised image-to-image translation tasks aim to find a mapping between a source domain X and a target domain Y from unpaired training data. Contrastive learning for Unpaired i…
Single Underwater Image Restoration by Contrastive Learning
Junlin Han, Mehrdad Shoeiby, Tim Malthus +6
Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world. This paper elaborates on a novel method that achieves state-of-…
Mosaic Super-resolution via Sequential Feature Pyramid Networks
Mehrdad Shoeiby, Mohammad Ali Armin, Sadegh Aliakbarian +2
Advances in the design of multi-spectral cameras have led to great interests in a wide range of applications, from astronomy to autonomous driving. However, such cameras inherently…
Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
Mehrdad Shoeiby, Lars Petersson, Mohammad Ali Armin +2
This paper introduces a novel method to simultaneously super-resolve and colour-predict images acquired by snapshot mosaic sensors. These sensors allow for spectral images to be ac…
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network
Mehrdad Shoeiby, Sadegh Aliakbarian, Saeed Anwar +1
This paper introduces a novel method to super-resolve multi-spectral images captured by modern real-time single-shot mosaic image sensors, also known as multi-spectral cameras. Our…