Semantic Example Guided Image-to-Image Translation

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Semiautomatic Image Retrieval Using the High Level Semantic Labels

Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

Novel Algorithm for Translation from Image Content to Semantic Form

In this paper we present a new algorithm for translating visual information into a semantic form. In our approach we try to combine these two separate areas of computer since into one process. The main goal is to achieve very good performance at searching for similar images. In this paper we explain in details the design of the translation algorithm which is only one part of the whole process, ...

Unsupervised Image-to-Image Translation Networks

Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains. Since there exists an infinite set of joint distributions that can arrive the given marginal distributions, one could infer nothing about the joint distribution from the marginal distributions without additional assum...

Image to Image Translation for Domain Adaptation

We propose a general framework for unsupervised domain adaptation, which allows deep neural networks trained on a source domain to be tested on a different target domain without requiring any training annotations in the target domain. This is achieved by adding extra networks and losses that help regularize the features extracted by the backbone encoder network. To this end we propose the novel...