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Yinzhi Cao*

2 accepted papers

2024

Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models

ECCV 2024poster

"Video Anomaly Detection (VAD) is crucial for applications such as security surveillance and autonomous driving. However, existing VAD methods provide little rationale behind detection, hindering public trust in real-world deployments. In this paper, we approach VAD with a reasoning framework. Altho…

2024

PFedEdit: Personalized Federated Learning via Automated Model Editing

ECCV 2024poster

"Federated learning (FL) allows clients to train a deep learning model collaboratively while maintaining their private data locally. One challenging problem facing FL is that the model utility drops significantly once the data distribution gets heterogeneous, or non-i.i.d, among clients. A promising…