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 …

Visualizations are now widely used across disciplines to understand and communicate data.
The benefit of visualizations lies in leveraging our natural visual perception. However, the …

To address the challenges of digital intelligence in the digital economy, artificial intelligence-
generated content (AIGC) has emerged. AIGC uses artificial intelligence to assist or replace …

The study of algorithms to automatically answer visual questions currently is motivated by
visual question answering (VQA) datasets constructed in artificial VQA settings. We propose …

Image captioning is one of the primary goals in computer vision which aims to automatically
generate natural descriptions for images. Intuitively, human visual system can notice some …

Current image captioning methods are usually trained via maximum likelihood estimation.
However, the log-likelihood score of a caption does not correlate well with human …

Abstract We propose Localized Narratives, a new form of multimodal image annotations
connecting vision and language. We ask annotators to describe an image with their voice …

While an important problem in the vision community is to design algorithms that can
automatically caption images, few publicly-available datasets for algorithm development …

Although AI holds promise for improving human decision making in societally critical
domains, it remains an open question how human-AI teams can reliably outperform AI alone …

In this paper, we examine computational approaches for measuring the" fairness" of image
tagging systems, finding that they cluster into five distinct categories, each with its own …