SAGHOG: Self-Supervised Autoencoder for Generating HOG Features for Writer Retrieval

arXiv:2404.17221v1 Announce Type: new
Abstract: This paper introduces SAGHOG, a self-supervised pretraining strategy for writer retrieval using HOG features of the binarized input image. Our preprocessing involves the application of the Segment Anything technique to extract handwriting from various datasets, ending up with about 24k documents, followed by training a vision transformer on reconstructing masked patches of the handwriting. SAGHOG is then finetuned by appending NetRVLAD as an encoding layer to the pretrained encoder. Evaluation of our approach on three …

abstract application arxiv autoencoder cs.cv datasets documents extract features handwriting image paper pretraining retrieval segment segment anything strategy training type writer