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20162020
most citedExploring Temporal Preservation Networks for Precise Temporal Action Localization

33 citations · 46 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2020

Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

Xuanzhao Wang, Zhengping Che, Bo Jiang +6

Video anomaly detection is commonly used in many applications such as security surveillance and is very challenging.A majority of recent video anomaly detection approaches utilize…

cs.CV20196 cited

Towards Precise End-to-end Weakly Supervised Object Detection Network

Ke Yang, Dongsheng Li, Yong Dou

It is challenging for weakly supervised object detection network to precisely predict the positions of the objects, since there are no instance-level category annotations. Most exi…

cs.CV2019

Exploring Frame Segmentation Networks for Temporal Action Localization

Ke Yang, Xiaolong Shen, Peng Qiao +3

Temporal action localization is an important task of computer vision. Though many methods have been proposed, it still remains an open question how to predict the temporal location…

cs.CV20197 cited

IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition

Ke Yang, Peng Qiao, Dongsheng Li +1

Effective spatiotemporal feature representation is crucial to the video-based action recognition task. Focusing on discriminate spatiotemporal feature learning, we propose Informat…

cs.CV201733 cited

Exploring Temporal Preservation Networks for Precise Temporal Action Localization

Ke Yang, Peng Qiao, Dongsheng Li +2

Temporal action localization is an important task of computer vision. Though a variety of methods have been proposed, it still remains an open question how to predict the temporal…

cs.CV2016

Relative distance features for gait recognition with Kinect

Ke Yang, Yong Dou, Shaohe Lv +2

Gait and static body measurement are important biometric technologies for passive human recognition. Many previous works argue that recognition performance based completely on the…