Search Results for author: Yi Qu

Found 4 papers, 3 papers with code

BatchNorm-based Weakly Supervised Video Anomaly Detection

1 code implementation26 Nov 2023 Yixuan Zhou, Yi Qu, Xing Xu, Fumin Shen, Jingkuan Song, HengTao Shen

In the proposed BN-WVAD, we leverage the Divergence of Feature from Mean vector (DFM) of BatchNorm as a reliable abnormality criterion to discern potential abnormal snippets in abnormal videos.

Anomaly Detection In Surveillance Videos Video Anomaly Detection

ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced Recognition

1 code implementation ICCV 2023 Yixuan Zhou, Yi Qu, Xing Xu, HengTao Shen

To overcome this bottleneck, we leverage class priors to restrict the generalization scope of the class-agnostic SAM and propose a class-aware smoothness optimization algorithm named Imbalanced-SAM (ImbSAM).

Semi-supervised Anomaly Detection Supervised Anomaly Detection

AnoOnly: Semi-Supervised Anomaly Detection with the Only Loss on Anomalies

1 code implementation30 May 2023 Yixuan Zhou, Peiyu Yang, Yi Qu, Xing Xu, Zhe Sun, Andrzej Cichocki

Unlike existing SSAD methods that resort to strict loss supervision, AnoOnly suspends it and introduces a form of weak supervision for normal data.

Semi-supervised Anomaly Detection Supervised Anomaly Detection +1

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