activity
20182026
most citedLearning on Attribute-Missing Graphs

126 citations · 292 across the 35 of their papers we have counts for

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Showing 2020Show all

20 papers · 1 filter

cs.CV2020

Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation

Chenxin Xu, Siheng Chen, Maosen Li +1

We propose a novel method based on teacher-student learning framework for 3D human pose estimation without any 3D annotation or side information. To solve this unsupervised-learnin…

cs.CV2020★ 11 cited

Point-Level Temporal Action Localization: Bridging Fully-supervised Proposals to Weakly-supervised Losses

Chen Ju, Peisen Zhao, Ya Zhang +2

Point-Level temporal action localization (PTAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance. Existing methods adopt the…

cs.CV2020

Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework

Fei Ye, Huangjie Zheng, Chaoqin Huang +1

Surrogate task based methods have recently shown great promise for unsupervised image anomaly detection. However, there is no guarantee that the surrogate tasks share the consisten…

cs.CV2020★ 7 cited

Privileged Knowledge Distillation for Online Action Detection

Peisen Zhao, Lingxi Xie, Ya Zhang +2

Online Action Detection (OAD) in videos is proposed as a per-frame labeling task to address the real-time prediction tasks that can only obtain the previous and current video frame…

cs.LG2020

ESAD: End-to-end Deep Semi-supervised Anomaly Detection

Chaoqin Huang, Fei Ye, Peisen Zhao +3

This paper explores semi-supervised anomaly detection, a more practical setting for anomaly detection where a small additional set of labeled samples are provided. We propose a new…

cs.LG2020★ 126 cited

Learning on Attribute-Missing Graphs

Xu Chen, Siheng Chen, Jiangchao Yao +3

Graphs with complete node attributes have been widely explored recently. While in practice, there is a graph where attributes of only partial nodes could be available and those of…