The multi-modal fusion in visual question answering: a review of attention mechanisms
Abstract Visual Question Answering (VQA) is a significant cross-disciplinary issue in the
fields of computer vision and natural language processing that requires a computer to output …
fields of computer vision and natural language processing that requires a computer to output …
An analysis of graph convolutional networks and recent datasets for visual question answering
AA Yusuf, F Chong, M Xianling - Artificial Intelligence Review, 2022 - Springer
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 …
structural scenarios due to its substantial performance and interpretability recently. In a non …
MRA-Net: Improving VQA via multi-modal relation attention network
Visual Question Answering (VQA) is a task to answer natural language questions tied to the
content of visual images. Most recent VQA approaches usually apply attention mechanism to …
content of visual images. Most recent VQA approaches usually apply attention mechanism to …
Dual self-attention with co-attention networks for visual question answering
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 …
language has been proposed and aroused wide interests. In previous VQA methods …
Scene graph refinement network for visual question answering
Visual Question Answering aims to answer the free-form natural language question based
on the visual clues in a given image. It is a difficult problem as it requires understanding the …
on the visual clues in a given image. It is a difficult problem as it requires understanding the …
A survey of methods, datasets and evaluation metrics for visual question answering
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 …
captured the attention of both computer vision as well as natural language processing …
Cascade reasoning network for text-based visual question answering
We study the problem of text-based visual question answering (T-VQA) in this paper. Unlike
general visual question answering (VQA) which only builds connections between questions …
general visual question answering (VQA) which only builds connections between questions …
DeltaNet: Conditional medical report generation for COVID-19 diagnosis
Fast screening and diagnosis are critical in COVID-19 patient treatment. In addition to the
gold standard RT-PCR, radiological imaging like X-ray and CT also works as an important …
gold standard RT-PCR, radiological imaging like X-ray and CT also works as an important …
Audio-visual event localization by learning spatial and semantic co-attention
C Xue, X Zhong, M Cai, H Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This work aims to temporally localize events that are both audible and visible in video.
Previous methods mainly focused on temporal modeling of events with simple fusion of …
Previous methods mainly focused on temporal modeling of events with simple fusion of …
CRA-Net: Composed relation attention network for visual question answering
The task of Visual Question Answering (VQA) is to answer a natural language question tied
to the content of a visual image. Most existing VQA models either apply attention mechanism …
to the content of a visual image. Most existing VQA models either apply attention mechanism …