no code implementations • journal 2021 • Shikha Dubey, Abhijeet Boragule, Jeonghwan Gwak, Moongu Jeon
We propose a framework, Deep-network with Multiple Ranking Measures(DMRMs), which addresses context-dependency using a joint learning technique for motion and appearance features.
Ranked #10 on Anomaly Detection In Surveillance Videos on UCF-Crime
no code implementations • 4 Feb 2020 • Shikha Dubey, Abhijeet Boragule, Moongu Jeon
Afterwards, using these features and deep multiple instance learning along with the proposed ranking loss, our model learns to predict the abnormality score at the video segment level.
Ranked #12 on Anomaly Detection In Surveillance Videos on UCF-Crime
no code implementations • 28 May 2018 • Young-chul Yoon, Abhijeet Boragule, Young-min Song, Kwangjin Yoon, Moongu Jeon
In this paper, we propose the methods to handle temporal errors during multi-object tracking.