29 citations · 38 across the 5 of their papers we have counts for
5 papers
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection
Jia-Xing Zhong, Nannan Li, Weijie Kong +3
Video anomaly detection under weak labels is formulated as a typical multiple-instance learning problem in previous works. In this paper, we provide a new perspective, i.e., a supe…
BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization
Weijie Kong, Nannan Li, Shan Liu +2
Despite tremendous progress achieved in temporal action detection, state-of-the-art methods still suffer from the sharp performance deterioration when localizing the starting and e…
Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector
Jia-Xing Zhong, Nannan Li, Weijie Kong +3
Weakly supervised temporal action detection is a Herculean task in understanding untrimmed videos, since no supervisory signal except the video-level category label is available on…
A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning
Jingjia Huang, Nannan Li, Tao Zhang +1
Existing action detection algorithms usually generate action proposals through an extensive search over the video at multiple temporal scales, which brings about huge computational…
Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking
Nannan Li, Dan Xu, Zhenqiang Ying +2
In this paper, we address the problem of searching action proposals in unconstrained video clips. Our approach starts from actionness estimation on frame-level bounding boxes, and…