computer-vision-3

Pornography Detection

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Spatiotemporal CNNs for Pornography Detection in Videos

Murilo Varges da Silva, A. Marana•Tue Oct 23 2018

Two spatiotemporal CNNs, VGG-C3D CNN and ResNet R(2+1)D CNN, were assessed for pornography detection in videos and performed better than some state-of-the-art methods based on bag of visual words and are competitive with other CNN-based approaches.

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A mid-level video representation based on binary descriptors: A case study for pornography detection

W. R. Schwartz, S. Avila, C. Caetano, S. Guimarães, A. Araújo•Wed May 11 2016

An approach for pornography detection based on local binary feature extraction and BossaNova image representation and a BoW model extension that preserves more richly the visual information is proposed, achieving an accuracy of 92.40%, and reducing the classification error by 16% over the current state-of-the-art local features approach.

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Combating the Elsagate Phenomenon: Deep Learning Architectures for Disturbing Cartoons

S. Avila, Akari Ishikawa, Edson R. Bollis•Wed Apr 17 2019

As the first to explore disturbing content in cartoons, this work proceeds from the most recent pornography detection literature applying deep convolutional neural networks combined with static and motion information of the video.

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