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DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

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arxiv 2506.05372 v1 pith:KXHDSKVO submitted 2025-05-29 cs.CV

Dimitrios Kollias , Damith C. Senadeera , Jianian Zheng , Kaushal K. K. Yadav , Greg Slabaugh , Muhammad Awais , Xiaoyun Yang This is my paper
classification cs.CV
keywords databasesdetectiondiverseexistinglimitedmetadatareal-worldviolence
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 5 Pith papers

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