https://github.com/rlleshi/phar
This is just a fun, side-project to see how State-of-the-art (SOTA) Human Action Recognition (HAR) models fare in the pornographic domain. HAR is a relatively new, active field of research in the deep learning domain, its goal being the identification of human actions from various input streams (e.g. video or sensor).
The pornography domain is interesting from a technical perspective because of its inherent difficulties. Light variations, occlusions, and a tremendous variations of different camera angles and filming techniques (POV, dedicated camera person) make position (action) recognition hard. We can have two identical positions (actions) and yet be captured in such a different camera perspective to entirely confuse the model in its predictions.
This repository uses three different input streams in order to get the best possible results: rgb frames, human skeleton, and audio. Correspondingly three different models are trained on these input streams and their results are merged through late fusion.
The best current accuracy reached by this multi-model model currently is 75.64%, which is promising considering the small training set. This result will be improved in the future.
The models work on spatio-temporal data, meaning that they processes video clips rather than single images (miles-deep is using single images for example). This is an inherently superior way of performing action recognition.
Currently, 17 actions are supported. You can find the complete list here. More data would be needed to further improve the models (help is welcomed). Read on for more information!
Motivation & Usages
The idea behind this project is to try and apply the latest deep learning techniques (i.e. human action recognition) in the pornographic domain.
Once we have detailed information about the kind of actions/positions that are happening in a video a number of uses-cases can apply:
Improving the recommender system
Automatic tag generator
Automatic timestamp generator (when does an action start and finish)
Cutting content out (for example non-sexual content)
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Snapshots:
undelete.pullpush.io
archive.org
archive.ph (click to archive)
ghostarchive.org (click to archive)
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More options
Context
Well, there’s a lot of it to run through with a lot of variation I guess?
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Context