研究者希望能够打破黑箱,探索神经网络在完成VQA (Visual Question Answering) 时能够显式的表达出推理过程,并根据这些推理阶段进行训练。这就是视觉推理(Visual Reasoning)。 CLEVR 斯坦福大学李飞飞团队提出了CLEVR数据集,专门针对视觉推理任务。 CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visu...
HGL for Visual Commonsense Reasoning 题目:Heterogeneous Graph Learning for Visual Commonsense Reasoning 来源:NeurIPS-2019 原文链接: https://arxiv.org/pdf/1910.11475.pdfarxiv.org/pdf/1910.11475.pdf Abstract 视觉常识推理任务(From Recognition to Cognition)旨在通过预测正确答案的能力同时需要提供令人信...
Human analogical reasoning is thought to be driven by similarity both at the relational level and at the basic object level26. This latter influence has often been framed as a deficiency in human reasoning—an inability to achieve the pure abstraction that would presumably be enabled by focusing ...
4.1 视觉常识推理(Visual Commonsense Reasoning, VCR) VCR任务给定一张标记了感兴趣区域的图像,并提出了一个问题,期望模型能根据问题和图像做出回答,并对回答给出进一步推理和解释。因此大体上可以分为两个子任务,第一个任务是根据问题进行回答\text{Q→A},第二个任务是根据问题和回答进行论证\text{QA→R}。 这...
文档格式: .pdf 文档大小: 1.3M 文档页数: 21页 顶/踩数: 0/0 收藏人数: 0 评论次数: 0 文档热度: 文档分类: IT计算机--.NET 系统标签: reasoningvisualdatasetannotatedfigurebokeh Workshoptrack-ICLR2018FIGUREQA:ANANNOTATEDFIGUREDATASETFORVISUALREASONINGSamiraEbrahimiKahou1∗,VincentMichalski2∗†,Adam...
Glass Onion : Visual Reasoning with Recommendation Systems through 3D Mnemonic MetaphorsRecommendation Systems3d Information VisualizationHCIThe Glass Onion is a project in its infancy. We aim to utilize the Recommendation Systems Model as a solution to oversaturation of data, and would like to explore...
Recent Papers including Neural Symbolic Reasoning, Logical Reasoning, Visual Reasoning, planning and any other topics connecting deep learning and reasoning - floodsung/Deep-Reasoning-Papers
Visual entailment is a recently proposed multimodal reasoning task where the goal is to predict the logical relationship of a piece of text to an image. In this paper, we propose an extension of this task, where the goal is to predict the logical relationship of fine-grained knowledge ...
2. Learning Alignments with Visual Semantic Reasoning: 算法的大致流程如下所示: 2.1. Image Representation by Bottom-Up Attention: 本文与 “Stacked Cross Attention for Image-Text Matching” 保持一致,也采用基于 faster RCNN 模型的 bottom-up attention 来得到图像中的物体或者显著性的区域。该模型是在 Vis...
In particular, as the purpose of any VQS is to provide access to the information contained in a database, the main users' tasks are understanding the database content, focusing on meaningful items, finding query patterns, and reasoning on the query result. The first graphical query language ...