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The Rijksmuseum Challenge: Museum-Centered Visual Recognition

Authors:

Thomas Mensink,

Jan van GemertAuthors Info & Claims

ICMR '14: Proceedings of International Conference on Multimedia Retrieval

Pages 451 - 454

https://doi.org/10.1145/2578726.2578791

Published: 01 April 2014 Publication History

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Abstract

This paper offers a challenge for visual classification and content-based retrieval of artistic content. The challenge is posed from a museum-centric point of view offering a wide range of object types including paintings, photographs, ceramics, furniture, etc. The freely available dataset consists of 112,039 photographic reproductions of the artworks exhibited in the Rijksmuseum in Amsterdam, the Netherlands. We offer four automatic visual recognition challenges consisting of predicting the artist, type, material and creation year. We include a set of baseline results, and make available state-of-the-art image features encoded with the Fisher vector. Progress on this challenge improves the tools of a museum curator while improving content-based exploration by online visitors of the museum collection.

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Cited By

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Wu YNakashima YGarcia N(2024)GOYA: Leveraging Generative Art for Content-Style DisentanglementJournal of Imaging10.3390/jimaging1007015610:7(156)Online publication date: 26-Jun-2024
https://doi.org/10.3390/jimaging10070156
Schneider SVollmer R(2024)Poses of People in Art: A Dataset for Human Pose Estimation in Digital Art HistoryJournal on Computing and Cultural Heritage 10.1145/369645517:4(1-19)Online publication date: 5-Dec-2024
https://dl.acm.org/doi/10.1145/3696455
Srinivasan R(2024)To See or Not to See: Understanding the Tensions of Algorithmic Curation for Visual ArtsProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658917(444-455)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658917
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Index Terms

The Rijksmuseum Challenge: Museum-Centered Visual Recognition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition
2. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Multimedia information systems

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Information & Contributors

Information

Published In

ICMR '14: Proceedings of International Conference on Multimedia Retrieval

April 2014

564 pages

ISBN:9781450327824

DOI:10.1145/2578726

Conference Chairs:
Mohan Kankanhalli
National University of Singapore
,
Stefan Rueger
The Open University, UK
,
R. Manmatha
A9.com, USA
,
General Chairs:
Joemon Jose
University of Glasgow, UK
,
Keith van Rijsbergen
University of Glasgow, UK

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2014

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ICMR '14

ICMR '14: International Conference on Multimedia Retrieval

April 1 - 4, 2014

Glasgow, United Kingdom

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ICMR '14 Paper Acceptance Rate 21 of 111 submissions, 19%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

View all

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https://doi.org/10.3390/jimaging10070156
Schneider SVollmer R(2024)Poses of People in Art: A Dataset for Human Pose Estimation in Digital Art HistoryJournal on Computing and Cultural Heritage 10.1145/369645517:4(1-19)Online publication date: 5-Dec-2024
https://dl.acm.org/doi/10.1145/3696455
Srinivasan R(2024)To See or Not to See: Understanding the Tensions of Algorithmic Curation for Visual ArtsProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658917(444-455)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658917
Springstein MSchneider SRahnama JStalter JKristen MMüller-Budack EEwerth R(2024)Visual Narratives: Large-scale Hierarchical Classification of Art-historical Images2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00705(7195-7205)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00705
Schmitt NLoesch YHoumani NGarcia-Salicetti S(2024)Transfer Learning for Artwork Attribution: Assessing the Importance of the Artist's Signature2024 IEEE Thirteenth International Conference on Image Processing Theory, Tools and Applications (IPTA)10.1109/IPTA62886.2024.10755887(01-07)Online publication date: 14-Oct-2024
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Florea LFlorea CVertan C(2024)Are Computers Able to Understand Art?Digital Transformation10.1007/978-3-031-55952-5_9(159-188)Online publication date: 27-Apr-2024
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Dobbs TNayeem ACho IRas Z(2023)Contemporary Art Authentication with Large-Scale ClassificationBig Data and Cognitive Computing10.3390/bdcc70401627:4(162)Online publication date: 9-Oct-2023
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Weng LGouet-Brunet VKosti RWeng L(2023)Beyond Built Year Prediction: The Bag of Time Model and a Case Study of Buddha ImagesProceedings of the 5th Workshop on analySis, Understanding and proMotion of heritAge Contents10.1145/3607542.3617352(59-67)Online publication date: 2-Nov-2023
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Wu YNakashima YGarcia N(2023)Not Only Generative Art: Stable Diffusion for Content-Style Disentanglement in Art AnalysisProceedings of the 2023 ACM International Conference on Multimedia Retrieval10.1145/3591106.3592262(199-208)Online publication date: 12-Jun-2023
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Becattini FBongini PBulla LBimbo AMarinucci LMongiovì MPresutti V(2023)VISCOUNTH: A Large-scale Multilingual Visual Question Answering Dataset for Cultural HeritageACM Transactions on Multimedia Computing, Communications, and Applications10.1145/359077319:6(1-20)Online publication date: 12-Jul-2023
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Dimensions of indigenous heritage discourse and the use of technologies of display in an ethnographic exhibition: a case study of the "Song for the Horse Nation" exhibition (National Museum of the American Indian, New York)

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