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 …

Image captioning is a research area of immense importance, aiming to generate natural
language descriptions for visual content in the form of still images. The advent of deep …

Abstract Skeleton-based Human Activity Recognition has achieved great interest in recent
years as skeleton data has demonstrated being robust to illumination changes, body scales …

Dynamic scene graph generation aims at generating a scene graph of the given video.
Compared to the task of scene graph generation from images, it is more challenging …

User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …

Variational autoencoder architectures have the potential to develop reduced-order models
for chaotic fluid flows. We propose a method for learning compact and near-orthogonal …

Automated radiographic report generation is challenging in at least two aspects. First,
medical images are very similar to each other and the visual differences of clinic importance …

Humans can not only see the collection of objects in visual scenes, but also identify the
relationship between objects. The visual relationship in the scene can be abstracted into the …

Existing image captioning methods just focus on understanding the relationship between
objects or instances in a single image, without exploring the contextual correlation existed …

Image captioning is shown to be able to achieve a better performance by using scene
graphs to represent the relations of objects in the image. The current captioning encoders …