Graph Neural Networks (GNNs) have gained momentum in graph representation learning
and boosted the state of the art in a variety of areas, such as data mining (eg, social network …

Graph neural network is a deep learning approach widely applied on structural and non-
structural scenarios due to its substantial performance and interpretability recently. In a non …

We present a new dataset for Visual Question Answering (VQA) on document images called
DocVQA. The dataset consists of 50,000 questions defined on 12,000+ document images …

We propose a novel multimodal architecture for Scene Text Visual Question Answering
(STVQA), named Layout-Aware Transformer (LaTr). The task of STVQA requires models to …

Abstract The Remote Embodied Referring Expression (REVERIE) is a recently raised task
that requires an agent to navigate to and localise a referred remote object according to a …

Given an image and a natural language question, Visual Question Answering (VQA) aims at
answering the textual question correctly. Most VQA approaches in literature targets at finding …

Existing open vocabulary object detection (OVD) works expand the object detector toward
open categories by replacing the classifier with the category text embeddings and optimizing …

Given a high-level instruction, the task of Embodied Referring Expression (REVERIE)
requires an embodied agent to localise a remote referred object via navigating in the …

Text-based visual question answering (TextVQA) requires analyzing both the visual contents
and texts in an image to answer a question, which is more practical than general visual …

Answering questions about complex situations in videos requires not only capturing of the
presence of actors, objects, and their relations, but also the evolution of these relationships …