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Their statement: http://image-net.org/update-sep-17-2019 http://image-net.org/update-sep-17-2019 > Each synset is classified as either “unsafe” (offensive reg
by orf 7y ago
Their statement: http://image-net.org/update-sep-17-2019 http://image-net.org/update-sep-17-2019
> Each synset is classified as either “unsafe” (offensive regardless of context), “sensitive” (offensive depending on context), or “safe”. “Unsafe” synsets are inherently offensive, such as those with profanity, those that correspond to racial or gender slurs, or those that correspond to negative characterizations of people (for example, racist). “Sensitive” synsets are not inherently offensive, but they may cause offense when applied inappropriately, such as the classification of people based on sexual orientation and religion.
> So far out of 2,832 synsets within the person subtree we’ve identified 438 “unsafe” synsets and 1,155 “sensitive” synsets. The remaining 1,239 synsets are temporarily deemed “safe.”
They've also completely disabled Imagenet downloads while they remedy this.
- esyir 7y agoGreat, I can see some of this being useless (some parts of the unsafe dataset), but if they cull the "sensitive" portion, this may induce performance regressions. I need to find an ImageNet archive now.
- buildbot 7y agoIt doesn't really touch the 1000 class "Imagenet" that's commonly used in computer vision.
- esyir 7y agoAh, then it's fine... probably.
- yorwba 7y agoSome of the classes are subcategories of ILSVRC classes in the WordNet hierarchy. So by removing images of persons in categories that are considered inappropriate, the resulting classifier will end up less likely to recognize those as images of people at all. I'm not sure whether that's a better outcome.
- kristianp 7y agoThis should be the link to the article.