This archive contains the anonymized version of the data used and introduced in [1].
It is a dataset of facial descriptors with their corresponding anonymized labels. All facial descriptors are also assigned to a program. The facial descriptors assignement to each programs is based on real TV shows broadcasted on French TV as detailed in [1].
The archive is a a tar.gz file split in 3 parts : dataset-anonymized-part00, dataset-anonymized-part01, dataset-anonymized-part02. You can merge them with the following command :
cat dataset-anonymized-part0* > dataset-anonymized.tar.gz
You can check the archive has been correctly merged with the md5 checksum in dataset-anonymized.tar.gz.md5 :
md5sum dataset-anonymized.tar.gz
This archives contains a training set and a test set, respectively 'anonymized_train.h5' and 'anonymized_test.h5'. The training set size is 548,686 and the test set size is 3,823. Each one of these archives has 3 fields : "programs", "identities" and "embeddings". The "programs" field contains program ids as integers. The "identities" field contains identity ids strings. The "embeddings" field contains 128-dimensional facial descriptors.
If you use this dataset please cite : [1] Thomas Petit, Pierre Letessier, Stefan Duffner, Christophe Garcia. 2020. Unsupervised learning of co-occurrences for face images retrieval. In 2020 ACM Multimedia Asia.
For any additional information, please contact (in this order or priority) : tpetit@ina.fr pletessier@ina.fr stefan.duffner@liris.cnrs.fr christophe.garcia@insa-lyon.fr