Inappropriate image detection is an essential component of online content moderation. It allows developers to automatically flag images that may contain explicit nudity, violence or drugs.
Prompt-tuning based on a dataset of socio-moral values steers CLIP to identify potentially inappropriate content, significantly reducing human effort. For example, a word cloud highlights frequent concepts such as gore or sexual content.
NSFW
The term NSFW is an abbreviation of “Not Safe for Work” or “Not Suitable for Work.” It’s used to label content that would be inappropriate in a professional setting. This kind of content is usually considered to be sexually explicit, contains curse words that would normally be bleeped out on network television or movies, or includes images of graphic violence. This kind of content is also known as triggering or upsetting, and it can cause someone to have an anxiety attack or even a physical reaction.
NSFW can be used as a tag for posts on social media, as a caption for a video, or in the header of an email. It’s important to label any inappropriate content as NSFW, so that it’s clear to the recipient what the material is about. This can prevent them from accidentally viewing the inappropriate content and potentially getting into trouble at work or in front of family members. It can also help avoid embarrassing conversations and reprimands.
In the early 2000s, NSFW was often used to flag content on Internet forums and chat services that was inappropriate for viewing in public spaces. This was particularly true in the case of forums that dealt with pornography. Since then, NSFW has been widely adopted on social media and other websites. It’s now common for NSFW to be used as a mark for content that should not be consumed in a professional setting or when children are around.
Despite the fact that most traditional offices are now a thing of the past, and people are mostly working from home or other remote locations, the term NSFW remains in common usage. It’s not so much about avoiding embarrassment or trouble with the beady eyes of those in authority, as it is about considering who is around when you view certain content.
Can a computer be trained to detect nude or NSFW images?
While it is possible for computers to learn to recognize images, it’s a very complicated task. The sensitivity of human skin and the differences between people’s skin tones mean that it is difficult for a computer to make accurate judgments about whether an image is inappropriate. This is why it’s important to have a human review any software that is intended to identify NSFW or nude images.
However, there is a lot of research being conducted into the use of AI to detect NSFW content. Advances in computer vision and deep learning are making it possible for computers to learn to recognize NSFW content with greater accuracy than humans.
Currently, most software designed to automatically identify NSFW images uses a model that focuses on identifying female nudity. This is based on the fact that female nudity is more likely to be considered inappropriate than male nudity. The researchers behind this study hope that they can expand the models to include male nudity and other types of inappropriate content. In the future, this type of technology could be used in a variety of applications, including medical imaging and facial recognition software.