Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection

no code implementations • 2 Mar 2024 • Chenchen Tao, Chong Wang, Yuexian Zou, Xiaohao Peng, Jiafei Wu, Jiangbo Qian

Most models for weakly supervised video anomaly detection (WS-VAD) rely on multiple instance learning, aiming to distinguish normal and abnormal snippets without specifying the type of anomaly.

Anomaly Detection Multiple Instance Learning +1

Split Two-Tower Model for Efficient and Privacy-Preserving Cross-device Federated Recommendation

no code implementations • 28 Jun 2022 • Jiangcheng Qin, Baisong Liu, Xueyuan Zhang, Jiangbo Qian

The server with the item model provides low-dimensional item embeddings instead of raw item data to the user devices for local training and online inferring, achieving server broadcast compression.

Federated Learning Privacy Preserving