Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …

Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …

Generating a description of an image is called image captioning. Image captioning requires
recognizing the important objects, their attributes, and their relationships in an image. It also …

Recent advances in deep learning have shown exciting promise in filling large holes in
natural images with semantically plausible and context aware details, impacting …

The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …

Learning a good image prior is a long-term goal for image restoration and manipulation.
While existing methods like deep image prior (DIP) capture low-level image statistics, there …

Object detection, scene graph generation and region captioning, which are three scene
understanding tasks at different semantic levels, are tied together: scene graphs are …

Generative convolutional deep neural networks, eg popular GAN architectures, are relying
on convolution based up-sampling methods to produce non-scalar outputs like images or …