use case: Similarity and reverse search
Although training AIs is already very easy, there are so many unknown people in many archives that even uploading three images of the respective person leads to a massive time investment. Thousands of hours of video material thus develop into a data silo whose already contained information cannot be used. Can DeepVA help me to store recurring persons, who currently cannot be named, so that they can be found in the future?
With the DeepVA Deep Indexer, unlabeled people are referenced as numbers and can then be retroactively labeled in the future. This is comparable to a huge memory card pile, the AI searches for pictures and videos of one person and classifies them as a dataset. In the end, the user only has to assign a name to the respective datasets, and you bring more structure into your archive material.
What results can be obtained?
faster data acquisition
Similarity and reverse search
Using Face Index, each person in video and image material can be assigned a number, allowing them to be translated into the metadata afterwards.
Enter your email below and we will get back to you as soon as possible.
Related use cases
don't miss the latest news!
Don’t worry, we reserve our newsletter for important news, so we only send a few updates once in a while. No spam!