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Calibrated Mixture-of-Experts Model Detailed

Modernity/arxiv 3h2h Impact 7
A new paper titled 'Reliability-Aware Prototype Calibration for Frozen Pose-Flow Video Anomaly Detection' has been published. The research focuses on pose-flow video anomaly detectors for one-class surveillance. The study outlines a novel approach to identifying unusual events in video streams. Authors include Luyang Fang and Xiaoming Zhai. Researchers have published a paper detailing a new method for pose-flow-based anomaly detection in videos. The model aims to align a model's predictive uncertainty with the frequencies of its empirical outcomes.

Topics

anomaly detection video surveillance AI

Developing

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Sources · 7 independent

Modernity/arxiv

“Reliability-Aware Prototype Calibration for Frozen Pose-Flow Video Anomaly Detection. Authors: Ning Dong, Yingna Su, Xin Dong, Ziyun Jiao, Xinnian Guo, Zhuangzhuang Pan Abstract: Pose-flow video anomaly detectors are attractive for one-class surveillance because they provide likelihoo...”

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Modernity/arxiv

“A new paper details pose-flow video anomaly detection.”

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Radio 4

“A new paper details pose-flow video anomaly detection.”

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Modernity/arxiv

“Toward Calibrated Mixture-of-Experts Under Distribution Shift. Authors: Gina Wong, Drew Prinster, Suchi Saria, Rama Chellappa, Anqi Liu Abstract: Calibration aligns a model's predictive uncertainty with the frequencies of its empirical outcomes and is important”

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