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 …
Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
卷积神经网络研究综述
李彦冬， 郝宗波， 雷航 - 计算机应用, 2016 - joca.cn
近年来, 卷积神经网络在图像分类, 目标检测, 图像语义分割等领域取得了一系列突破性的研究
成果, 其强大的特征学习与分类能力引起了广泛的关注, 具有重要的分析与研究价值 …
成果, 其强大的特征学习与分类能力引起了广泛的关注, 具有重要的分析与研究价值 …
Multiscale feature extraction and fusion of image and text in VQA
Abstract The Visual Question Answering (VQA) system is the process of finding useful
information from images related to the question to answer the question correctly. It can be …
information from images related to the question to answer the question correctly. It can be …
Knowledge base graph embedding module design for Visual question answering model
In this paper, a knowledge base graph embedding module is constructed to extend the
versatility of knowledge-based VQA (Visual Question Answering) models. The knowledge …
versatility of knowledge-based VQA (Visual Question Answering) models. The knowledge …
Howto100m: Learning a text-video embedding by watching hundred million narrated video clips
Learning text-video embeddings usually requires a dataset of video clips with manually
provided captions. However, such datasets are expensive and time consuming to create and …
provided captions. However, such datasets are expensive and time consuming to create and …
Ok-vqa: A visual question answering benchmark requiring external knowledge
Abstract Visual Question Answering (VQA) in its ideal form lets us study reasoning in the
joint space of vision and language and serves as a proxy for the AI task of scene …
joint space of vision and language and serves as a proxy for the AI task of scene …
Krisp: Integrating implicit and symbolic knowledge for open-domain knowledge-based vqa
One of the most challenging question types in VQA is when answering the question requires
outside knowledge not present in the image. In this work we study open-domain knowledge …
outside knowledge not present in the image. In this work we study open-domain knowledge …
Cascade r-cnn: Delving into high quality object detection
Z Cai, N Vasconcelos - … of the IEEE conference on computer …, 2018 - openaccess.thecvf.com
In object detection, an intersection over union (IoU) threshold is required to define positives
and negatives. An object detector, trained with low IoU threshold, eg 0.5, usually produces …
and negatives. An object detector, trained with low IoU threshold, eg 0.5, usually produces …
Multimodal intelligence: Representation learning, information fusion, and applications
Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …
natural language processing since 2010. Each of these tasks involves a single modality in …