Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal

时间 2021-01-07

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论文传送门作者北京大学机器感知与智能教育部重点实验室 Siming Chen Xiaoru Yuan 奇虎360 Zuchao Wang 悉尼科技大学 Jie Liang 摘要在分析人类行为时，我们需要从多个数据源构建人类行为，例如轨迹数据、交易数据、身份数据等。我们面临的问题是数据冲突、分辨率不同、数据缺失和冲突，这些问题共同导致了时空数据的不确定性。数据中的这种不确定性导致用于分析人的行

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1. Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal
2. CVPR 2018 STRCF:《Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking》论文笔记
3. [骨架动作识别]STA-LSTM: Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data
4. Spatial-Temporal Relation Networks for Multi-Object Tracking
5. Human Resources Analytics -- Kaggle Dataset
6. StNet: Local and Global spatial-temporal modeling for action regcognition
7. StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
8. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
9. (转) Exploring How Cache Coherency Accelerates Heterogeneous Compute
10. Exploring Visual Relationship for Image Captioning论文笔记

>>更多相关文章<<