#StackBounty: #dataset #model #computer-vision #object-detection What would be the ideal dataset to train a model to detect advertiseme…

Bounty: 100

I am thinking of the requirements for training a model that would be able to detect if there is any kind of ad in an image.

I know that this sound too broad not just for a question on CV but for the model itself.

There are numerous problems like:

  • The non-standard format of advertisements.
  • The fact that ads can also contain pictures apart from plain text, which apparently will display some objects.
  • Also the fact that in most cases are part of other objects, for example the frontpage of a magazine, the picture of a tv for a given moment, the contents of a billboard, a leaflet on the front windshield of a car, etc…

Still I’d like to make an attempt, so I am thinking what should be the ideal dataset to train a model for this task.

What I’ve come up with is to use a dataset of company logos and train a model to detect logos in picture.

Yet this strategy would eventually lead to more problems like

  • The false positive due to the fact that company logos exist also on the products sold apart from the product advertisements. This particular problem could be solved if there was a way to configuring the model to mark an object(a logo in this case) only if it occupied a portion of the picture larger than X%, since for example a logo on a car is relatively small compared to the car in contrast to the proportions of a car and a company logo in a magazine advertisement.

So, any ideas on which criteria should I take into consideration to create a useful dataset for this task are welcome.


Get this bounty!!!

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