Learning to Detect Violent Videos using Convolutional Long Short-Term Memory

The source code associated with the paper Learning to Detect Violent Videos using Convolutional Long Short-Term Memory, published in AVSS-2017. (Experimental release)

Prerequisites

• Python 3.5
• Pytorch 0.3.0

Running

python main-run-vr.py --numEpochs 100 \
--lr 1e-4 \
--stepSize 25 \
--decayRate 0.5 \
--seqLen 20 \
--trainBatchSize 16 \
--memSize 256 \
--evalInterval 5 \
--evalMode horFlip \
--numWorkers 4 \
--outDir violence \
--fightsDirTrain fightSamplesTrainDir \
--noFightsDirTrain noFightSamplesTrainDir \
--fightsDirTest fightSamplesTestDir \
--noFightsDirTest noFightSamplesTestDir

The images should be arranged in the following way:

To cite our paper/code:

@inproceedings{sudhakaran2017learning,
  title={Learning to detect violent videos using convolutional long short-term memory},
  author={Sudhakaran, Swathikiran and Lanz, Oswald},
  booktitle={Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on},
  pages={1--6},
  year={2017},
  organization={IEEE}
}