Hugging Face Trending Papers August 5, 2026

VQ-VAD: Vector-quantized Motion Representation Learning for Human-centric Video Anomaly Detection

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Video Anomaly Detection (VAD) is inherently challenging due to the scarcity of anomalies and the large visual variability in surveillance footage, including changes in lighting, viewpoint, and human appearance. To mitigate visual noise and address privacy concerns, recent work has shifted to pose-based VAD, which focuses on motion dynamics rather than raw video data.

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