Methodologies and Applications of Image Understanding in Cultural and Artistic Heritage

Dear Colleagues,

This Special Issue is dedicated to the various challenges and possibilities, both in terms of methodology and application, that emerge when computational methods are used to study, analyze, and interpret images in the context of art and culture. 

What does it mean to understand an image? The application of computational methods, such as object detection, segmentation, or classification, to images is usually motivated by the need to solve a particular problem. In the context of computer vision and deep learning, these methods are usually applied to general-purpose image datasets (ImageNet, MS Coco, etc.) or domain-specific image datasets (medical, satellite, traffic, etc.). Images related to art or cultural heritage may also represent another type of domain-specific image dataset. However, understanding an image becomes a much more complex task if we aim to integrate computational approaches of image understanding with the methodological and theoretical frameworks of traditional disciplines dedicated to the study of images in art and culture (e.g., art history and cultural and visual studies).

This Special Issue invites contributions that address different aspects of image understanding with the common goal of bridging cross-disciplinary gaps.

The topics of interest include, but are not limited to, the following:

• Computational analysis of images as visual cultural artifacts;
• Contextually meaningful image searches and similarity retrieval in artwork collections;
• Deep learning-based approaches for studying artwork images;
• Computer vision applications in cultural heritage;
• Multimodal deep learning for image understanding;
• Understanding AI-generated images in the context of art and culture.

Dr. Eva Cetinic
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• computer vision
• deep learning
• artwork analysis
• cultural heritage
• generative AI
• multimodality
• cultural AI
• art datasets
• digital art history
• digital visual studies