Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach

06/10/2021
by   Adrià Molina, et al.
2

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.

READ FULL TEXT

page 7

page 8

page 13

page 14

research
04/08/2022

A Generic Image Retrieval Method for Date Estimation of Historical Document Collections

Date estimation of historical document images is a challenging problem, ...
research
06/19/2019

Automatic estimation of heading date of paddy rice using deep learning

Accurate estimation of heading date of paddy rice greatly helps the bree...
research
06/22/2019

Image Retrieval and Pattern Spotting using Siamese Neural Network

This paper presents a novel approach for image retrieval and pattern spo...
research
04/07/2013

Image Retrieval using Histogram Factorization and Contextual Similarity Learning

Image retrieval has been a top topic in the field of both computer visio...
research
02/20/2023

iQPP: A Benchmark for Image Query Performance Prediction

To date, query performance prediction (QPP) in the context of content-ba...
research
10/19/2020

Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning

Remote sensing image retrieval (RSIR) is the process of ranking database...
research
05/09/2023

Unsupervised Writer Retrieval using NetRVLAD and Graph Similarity Reranking

This paper presents an unsupervised approach for writer retrieval based ...

Please sign up or login with your details

Forgot password? Click here to reset