Aug 9, 2023 · In this paper, we present a novel method named Multi-view attention relation network (MVARN) to improve the performance of the FQA task.
FQA aims to solve the problem of answering questions related to scientifically designed charts. In this study, we propose a novel model, called the Multi-view ...
In this regard, we propose a self-paced class-discriminative generative adversarial network incorporating multimodality in the context of few-shot learning. The ...
Aug 6, 2022 · We propose a novel algorithm called Multi-attention Relation Network (MARN), which consists of a CBAM module, an LSTM module, and an attention relation module.
Jul 7, 2021 · This paper proposes a multi-view attention-based model(MuVAM) for medical visual question answering which integrates the high-level semantics of medical images.
Missing: MVARN: Relation Network Figure
Generative AI for visualization: State of the art and future directions. Article. May 2024 ; MVARN: Multi-view Attention Relation Network for Figure Question ...
Figure 1. Overview of the multi-level attention network (MLAN). The proposed attention model highlights both question-related se- mantic concepts (i.e. ...
Missing: MVARN: | Show results with:MVARN:
Sep 7, 2022 · We propose a path attention memory network (PAM) to construct a more robust composite attention model.
Missing: MVARN: | Show results with:MVARN:
... Relation Triplet Extraction -- MVARN: Multi-view attention relation network for figure question answering -- MAGNN-GC: Multi-Head Attentive Graph Neural ...
MVARN: Multi-view Attention Relation Network for Figure Question Answering. Figure Question Answering (FQA) is an emerging multimodal task that shares ...