Video retrieval with CNN features
Résumé
Convolutional neural network features are becoming the norm in instance retrieval. This work investigate the relevance of using an of the shelf object detection network like Faster R-CNN as a feature extractor. We build an Image-to-video face retrieval pipeline composed of filtering and re-ranking that uses the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN. Moreover we study the relevance of features from a finetuned network. The results obtained are very promising
Origine | Fichiers produits par l'(les) auteur(s) |
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