A deep translation (GAN) based change detection network for optical and SAR remote sensing images
With the development of space-based imaging technology, a larger and larger number of
images with different modalities and resolutions are available. The optical images reflect the …
images with different modalities and resolutions are available. The optical images reflect the …
Image-to-image translation: Methods and applications
Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …
domain while preserving the content representations. I2I has drawn increasing attention and …
Unsupervised image-to-image translation: A review
Supervised image-to-image translation has been proven to generate realistic images with
sharp details and to have good quantitative performance. Such methods are trained on a …
sharp details and to have good quantitative performance. Such methods are trained on a …
Dual contrastive learning for unsupervised image-to-image translation
J Han, M Shoeiby, L Petersson… - Proceedings of the …, 2021 - openaccess.thecvf.com
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 …
domain X and a target domain Y from unpaired training data. Contrastive learning for …
Breaking the dilemma of medical image-to-image translation
L Kong, C Lian, D Huang, Y Hu… - Advances in Neural …, 2021 - proceedings.neurips.cc
Abstract Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that
dominate the field of medical image-to-image translation. However, neither modes are ideal …
dominate the field of medical image-to-image translation. However, neither modes are ideal …
Sketch2Photo: Synthesizing photo-realistic images from sketches via global contexts
H Liu, Y Xu, F Chen - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Sketch-to-image synthesis aims to generate realistic images that match the input sketches or
edge maps exactly. Most known sketch-to-image synthesis methods use various generative …
edge maps exactly. Most known sketch-to-image synthesis methods use various generative …
Learning to generate line drawings that convey geometry and semantics
This paper presents an unpaired method for creating line drawings from photographs.
Current methods often rely on high quality paired datasets to generate line drawings …
Current methods often rely on high quality paired datasets to generate line drawings …
Facial-sketch synthesis: A new challenge
This paper aims to conduct a comprehensive study on facial-sketch synthesis (FSS).
However, due to the high cost of obtaining hand-drawn sketch datasets, there is a lack of a …
However, due to the high cost of obtaining hand-drawn sketch datasets, there is a lack of a …
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation
Abstract Domain Adaptation (DA) has recently been of strong interest in the medical imaging
community. While a large variety of DA techniques have been proposed for image …
community. While a large variety of DA techniques have been proposed for image …
Concatenated deep learning framework for multi-task change detection of optical and sar images
Optical and synthetic aperture radar (SAR) images provide complementary information to
each other. However, the heterogeneity of same-ground objects brings a large difficulty to …
each other. However, the heterogeneity of same-ground objects brings a large difficulty to …