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RSS订阅原创 TRAR：Routing the attention spans in transformer for visual question answering学习笔记
问题：如何动态调度全局和局部依赖关系建模解决方法：基于实例的路由方案——TRAR。在TRAR中，每个视觉transformer层都配备了具有不同注意广度的路由模块。该模型可以根据前一步推理的输出动态选择相应的注意，以为每个实例制定最优路由路径。
2023-07-05 16:54:41
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原创 Iterative visual reasoning beyond convolutions （超越卷积的迭代视觉推理）
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition （CVPR）AbstractIntroductionIntroductionReasoning frameworkReasoning with convolutionsBeyond convolutionsIterative reasoningAttentionTrainingExperimentsDatasets and graphsTask and evaluation
2020-12-09 17:27:56
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原创 On exploring undetermined relationships for visual relationship detection（视觉关系检测中的不确定性关系研究）
目录AbstractIntroductionMF-URLNobject detectorundetermined relationship generatorundetermined relationship learning networkmulti-modal feature extraction networkrelationship learning networkExperiments2019 IEEE/CVF Conference on Computer Vision and Pattern
2020-12-08 17:56:35
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原创 Estimation of Visual Contents based on Question Answering from Human Brain Activity（基于人脑活动问答的视觉内容估计）
目录AbstractIntroductionVQA from fMRI datafMRI Decoder with Utilizing Un-labeled ImagesVQA from fMRI dataExperimental ResultsExperimental ConditionsPerformance EvaluationConclusionsAbstract提出了一种基于人脑活动的自由形式VQA估计方法，即大脑解码VQA。该方法可以在观看同一幅图像时实现回答任意来自功能磁共振成像（fMRI
2020-11-19 17:28:02
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原创 Visual Relationship Detection with a Deep Convolutional Relationship Network （基于深度卷积关系网络的视觉关系检测）
目录AbstractIntroductionProposed MethodOverview of Our FrameworkObject Detection ModuleRelationship Inference ModuleActivation FunctionPair filterExperiments of Our DCR ModelTask SettingEvaluation MetricsComparison with state-of-the-art MethodsAblation Study
2020-11-18 16:40:34
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原创 ALSA: Adversarial Learning of Supervised Attentions for VQA （VQA中有监督注意的对抗学习）
目录AbstractIntroductionRelated WorkVQAAdversarial LearningALSA for VQAProblem StatementSupervised Attention ModelsAdversarial Attention LearningOptimization for Answer PredictionExperimentsDatasets and BaselinesExperimental Settings and Evaluation MethodsRe
2020-11-17 17:10:29
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原创 VC-VQA: Visual Calibration Mechanism for Visual Question Answering （VQA的视觉校准机制）
目录AbstractIntroductionMethodOverviewVQA moduleReconstruction moduleLoss functionExperimentsAblation studiesPerformance on VQA v1 and VQA v2 datasetConclusion总结Abstract最近，许多研究指出VQA模型容易被数据集偏差所误导，并且严重依赖问题和答案之间的浅层关系，而不是真正理解视觉内容。为了解决这一问题，本文提出了视觉校准机制（VC-VQA），它
2020-11-06 16:48:07
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原创 Prior Visual Relationship Reasoning for Visual Question Answering（VQA中的先验视觉关系推理）
Prior Visual Relationship Reasoning for Visual Question Answering（VQA中的先验视觉关系推理）目录Prior Visual Relationship Reasoning for Visual Question Answering（VQA中的先验视觉关系推理）AbstractIntroductionMethodologyExperimental StudiesDatasets and MetricsConclusions总结Abstract
2020-11-05 17:50:54
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