Abstract The Visual Question Answering (VQA) task aspires to provide a meaningful testbed
for the development of AI models that can jointly reason over visual and natural language …

Image descriptions can help visually impaired people to quickly understand the image
content. While we made significant progress in automatically describing images and optical …

Abstract Large-scale Vision-and-Language (V+ L) pre-training for representation learning
has proven to be effective in boosting various downstream V+ L tasks. However, when it …

Vision and language representation learning has been demonstrated to be an effective
means of enhancing multimodal task performance. However, fashion-specific studies have …

Question Answering (QA) enables the machine to understand and answer questions posed
in natural language, which has emerged as a powerful tool in various domains. However …

Multimodal learning, here defined as learning from multiple input data types, has exciting
potential for healthcare. However, current techniques rely on large multimodal datasets …

Over the years, memes became very popular as social media services growing rapidly.
Understanding meme images as humans do is very complicated because of its multi-modal …

The paper considers the automatic analysis problem of a user's natural language query from
an image. The mechanism synthesizes a logically correct non-binary response. Synthesis is …

Few current image captioning systems are capable to read and integrate read text into the
generated descriptions, none of them was developed to solve the problem from a bilingual …

Homing, synchronizing and distinguishing sequences (HSs, SSs, and DSs) are used in FSM
(Finite State Machine) based testing for state identification and can significantly reduce the …