Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

Graph transformers are a recent advancement in machine learning, offering a new class of
neural network models for graph-structured data. The synergy between transformers and …

Image captioning aims to generate a description of a given image. However, inherent
representation differences between images and sentences make it difficult to align semantic …

Radiology report generation aims to automatically generate clinical descriptions for
radiology images, reducing the workload of radiologists. Compared to general image …

Situation recognition refers to the ability of an agent to identify and understand various
situations or contexts based on available information and sensory inputs. It involves the …

In recent years, significant progress has been made in visual-linguistic multi-modality
research, leading to advancements in visual comprehension and its applications in …

Abstract 3D dense captioning has received increasing attention in the multimodal field of 3D
vision and language. This task aims to generate a specific descriptive sentence for each …

Pretrained large vision-language models have shown outstanding performance on the task
of image captioning. However, owing to the insufficient decoding of image features, existing …

The emergence of Edge Computing has shifted the processing capabilities in proximity to
the Internet of Things data sources, offering solutions to latency and bandwidth constraints …

Learning to compose visual relationships from raw images in the form of scene graphs is a
highly challenging Computer Vision task, yet it is essential for applications related to scene …