DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios
Abstract
A large-scale violence detection database with frame-level annotations and diverse real-world conditions is introduced to improve model generalization and overcome limitations of existing datasets.
Violence Detection (VD) has become an increasingly vital area of research. Existing automated VD efforts are hindered by the limited availability of diverse, well-annotated databases. Existing databases suffer from coarse video-level annotations, limited scale and diversity, and lack of metadata, restricting the generalization of models. To address these challenges, we introduce DVD, a large-scale (500 videos, 2.7M frames), frame-level annotated VD database with diverse environments, varying lighting conditions, multiple camera sources, complex social interactions, and rich metadata. DVD is designed to capture the complexities of real-world violent events.
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