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RWF-2000: An Open Large Scale Video Database for Violence Detection

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In recent years, surveillance cameras are widely deployed in public places, and the general crime rate has been reduced significantly due to these ubiquitous devices. Usually, these cameras provide cues and evidence after crimes are conducted, while they are rarely used to prevent or stop criminal activities in time. It is both time and labor consuming to manually monitor a large amount of video data from surveillance cameras. Therefore, automatically recognizing violent behaviors from video signals becomes essential. This paper summarizes several existing video datasets for violence detection and proposes the RWF-2000 database with 2,000 videos captured by surveillance cameras in real-world scenes. Also, we present a new method that utilizes both the merits of 3D-CNNs and optical flow, namely Flow Gated Network. The proposed approach obtains an accuracy of 87.25% on the test set of our proposed database. The database and source codes are currently open to access.

Ming Cheng, Kunjing Cai, Ming Li• 2019

Related benchmarks

TaskDatasetResultRank
Violence DetectionHockey Fight
Accuracy98
43
Violence DetectionCrowd Violence
Accuracy88.87
26
Violence DetectionMovies Fight
Accuracy100
20
Violence DetectionRWF-2000
Accuracy87.3
17
Violence DetectionRWF
Accuracy87.2
12
Violence DetectionRWF-2000 2020
Accuracy87.5
7
Action RecognitionRWF-2000
Accuracy83.4
4
Action RecognitionHockey Fight
Accuracy0.934
4
Action RecognitionCrowd Violence
Accuracy83.4
4
Action RecognitionMovies Fight
Accuracy95.8
4
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