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metadata
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': 1930s
            '1': 1940s
            '2': 1950s
            '3': 1960s
            '4': 1970s
  splits:
    - name: train
      num_bytes: 221261063
      num_examples: 1325
  download_size: 222265856
  dataset_size: 221261063
pretty_name: Dating historical color images
task_categories:
  - image-classification
tags:
  - 'history '
  - lam
size_categories:
  - 1K<n<10K

Dataset Card for Dating historical color images

Table of Contents

Dataset Description

Dataset Summary

We introduce the task of automatically estimating the age of historical color photographs. We suggest features which attempt to capture temporally discriminative information based on the evolution of color imaging processes over time and evaluate the performance of both these novel features and existing features commonly utilized in other problem domains on a novel historical image data set. For the challenging classification task of sorting historical color images into the decade during which they were photographed, we demonstrate significantly greater accuracy than that shown by untrained humans on the same data set. Additionally, we apply the concept of data-driven camera response function estimation to historical color imagery, demonstrating its relevance to both the age estimation task and the popular application of imitating the appearance of vintage color photography.

Supported Tasks and Leaderboards

This dataset is intended to train image classification or regression models to predict the time period in which color photographs were taken. The task could be approached either as a classification task or could be approached as an image regression task.

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

There is a single training split since the original dataset doesn't define a train-test split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

Thanks to @github-username for adding this dataset.