Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

In order to answer semantically-complicated questions about an image, a Visual Question
Answering (VQA) model needs to fully understand the visual scene in the image, especially …

We present a novel unsupervised feature representation learning method, Visual
Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an …

Abstract Visual Question Answering (VQA) has emerged as an important problem spanning
Computer Vision, Natural Language Processing and Artificial Intelligence (AI). In …

A simultaneous understanding of questions and images is crucial in Visual Question
Answering (VQA). While the existing models have achieved satisfactory performance by …

Abstract Visual Question Answering (VQA) as an important task in understanding vision and
language has been proposed and aroused wide interests. In previous VQA methods …

Image and sentence matching has drawn much attention recently, but due to the lack of
sufficient pairwise data for training, most previous methods still cannot well associate those …

Scene graph generation models understand the scene through object and predicate
recognition, but are prone to mistakes due to the challenges of perception in the wild …

Abstract Visual Question Answering (VQA) is a multi-disciplinary research problem that has
captured the attention of both computer vision as well as natural language processing …