Date Estimation In The Wild Of Scanned Historical Photos: An Image Retrieval Approach
Adrià Molina, Pau Riba, Lluis Gomez, Oriol Ramos-Terrades, Josep Lladós . Lecture Notes in Computer Science 2021 – 0 citations
[Paper]
This paper presents a novel method for date estimation of historical photographs from archival sources. The main contribution is to formulate the date estimation as a retrieval task, where given a query, the retrieved images are ranked in terms of the estimated date similarity. The closer are their embedded representations the closer are their dates. Contrary to the traditional models that design a neural network that learns a classifier or a regressor, we propose a learning objective based on the nDCG ranking metric. We have experimentally evaluated the performance of the method in two different tasks: date estimation and date-sensitive image retrieval, using the DEW public database, overcoming the baseline methods.