Generative image completion with image-to-image translation
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04253-2
Abstract: Though many methods have been proposed, image completion still remains challenge; besides textured patterns completion, it often requires high-level understanding of scenes and objects being completed. More recently, deep convolutional generative adversarial networks have been… read more here.
Keywords: image; completion; image completion; image image ... See more keywords
Multidomain image-to-image translation model based on hidden space sharing
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-06386-9
Abstract: Image-to-image translation translates an image from one domain to another. The goal is to learn the translation relationship between different image domains. Compared with the translation models to be trained using paired training data, CycleGAN… read more here.
Keywords: image; hidden space; model; translation ... See more keywords
Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging
Sign Up to like & getrecommendations! Published in 2019 at "Radiological Physics and Technology"
DOI: 10.1007/s12194-019-00520-y
Abstract: Since the advent of deep convolutional neural networks (DNNs), computer vision has seen an extremely rapid progress that has led to huge advances in medical imaging. Every year, many new methods are reported at conferences… read more here.
Keywords: image; neural networks; medical imaging; image image ... See more keywords
Adversarial-learning-based image-to-image transformation: A survey
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.06.067
Abstract: Abstract Recently, the generative adversarial network (GAN) has attracted wide attention for various computer vision tasks. GAN provides a novel concept for image-to-image transformation by means of adversarial learning. In recent years, numerous adversarial-learning-based methods… read more here.
Keywords: image; image transformation; image image; learning based ... See more keywords
Asymmetric CycleGAN for image-to-image translations with uneven complexities
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DOI: 10.1016/j.neucom.2020.07.044
Abstract: Abstract CycleGAN is one of the famous and basic methods for unpaired image-to-image translation tasks. Inspired by the experiments of the NIR-RGB translation, which is a kind of translation where images are translated from simple… read more here.
Keywords: image; asymmetric cyclegan; cyclegan image; translation ... See more keywords
The body as image: image as body
Sign Up to like & getrecommendations! Published in 2017 at "The Lancet"
DOI: 10.1016/s0140-6736(17)30828-0
Abstract: Pain consultations are often contested spaces where patient and clinician compete for the roles of speaker. Often patients are searching for mechanical explanations and clinicians for psychological ones - creating an impasse and causing distress… read more here.
Keywords: image; body image; image body; pain ... See more keywords
Consistent Embedded GAN for Image-to-Image Translation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2939654
Abstract: Generative Adversarial Networks (GANs) have achieved remarkable progress in image-to-image translation tasks. However, these methods have the common problem that lacking the ability to generate both perceptually realistic and diverse images in the target domain.… read more here.
Keywords: image; consistent embedded; image image; image translation ... See more keywords
A Semi-Supervised Image-to-Image Translation Framework for SAR–Optical Image Matching
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3223353
Abstract: Synthetic aperture radar (SAR) and optical image matching aims to acquire correspondences from a certain pair of SAR and optical images. Recent advances in the image-to-image translation provided a way to simplify the SAR–optical image… read more here.
Keywords: sar optical; optical image; image image; image translation ... See more keywords
Unpaired Image-to-Image Translation Using Negative Learning for Noisy Patches
Sign Up to like & getrecommendations! Published in 2022 at "IEEE MultiMedia"
DOI: 10.1109/mmul.2022.3177452
Abstract: Unpaired image-to-image translation finds a mapping between two domains that do not have paired data. One approach is patchwise contrastive learning, a one-sided translation that maximizes mutual information between corresponding input and output patches. Noncorresponding… read more here.
Keywords: image image; image translation; negative learning; image ... See more keywords
Random Reconstructed Unpaired Image-to-Image Translation
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3160705
Abstract: The goal of unpaired image-to-image translation is to learn a mapping from a source domain to a target domain without using any labeled examples of paired images. This problem can be solved by learning the… read more here.
Keywords: image image; image translation; random reconstructed; image ... See more keywords
Multi-Constraint Adversarial Networks for Unsupervised Image-to-Image Translation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3144886
Abstract: Unsupervised image-to-image translation aims to learn the mapping from an input image in a source domain to an output image in a target domain without paired training dataset. Recently, remarkable progress has been made in… read more here.
Keywords: unsupervised image; image translation; image image; generator ... See more keywords