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The authors may want to consider how much of this work could be done easily and effectively with deep learning. For content-based search and image similarity, e
by zetazzed 11y ago
The authors may want to consider how much of this work could be done easily and effectively with deep learning. For content-based search and image similarity, even simple, pre-trained convnets will likely crush the histogram-based approaches you have here.
Just run your images through Google Cloud vision to do the face detection and text detection. With 2M images, it will be cheaper than the amount of dev time you spent here, and you'll get excellent quality.
- maciejgryka 11y agoIt would be awesome if they released this data for another edition of the Netflix challenge, Then we could all try this ourselves!
- TTPrograms 11y agoThey explain that not all of the images they want are faces in this case, so you'd have to train your own on "interesting regions" (though there is some work in that area). Part of the challenge in that case is generating all your labels for what the interesting regions are. This way they don't need to generate labels, at least.
- aab0 11y agoYoutube did something similar for 'interesting thumbnails' last year with deep nets (many uploaders do not specify a good thumbnail preview), and reported that it gave a nice performance boost.
- shekkizh 11y agoMy thoughts as well. With the recent advances doing image similarity and content based search should be fairly simple and probably more effective with pre-trained convnets.