Papers by Shengping Song

1 papers
CMHKF: Cross-Modality Heterogeneous Knowledge Fusion for Weakly Supervised Video Anomaly Detection (2025.acl-long)

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Challenge: Existing methods focus mainly on visual modalities, neglecting rich multi-modality information.
Approach: They propose a framework that integrates cross-modality knowledge from video, audio and text to improve anomaly detection and localization.
Outcome: The proposed framework improves detection and localization of anomalies using video-level labels.

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