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Vision for Art

VISART VII

Workshop at the European Conference of Computer Vision (ECCV)

Milan (Italy), Half-Day on 29th/30th September 2024

Call for Papers


Following the success of the previous editions of the Workshop on Computer VISion for ART held in 2012, `14, `16, `18, `20, `22 we present VISART VII. VISART will continue its role as a forum for the presentation, discussion and publication of Computer Vision (CV) techniques for the understanding of art. The explosion in the generative art, digitization of artworks and digitally-born art highlights the importance of application in the overlap between CV and art; such as ways to reason, connecting language, structuring data (i.e. databases) for Art to Cultural Heritage.

As with the prior edition, VISART VII offers two tracks:

1. Computer Vision for Art - technical work (standard ECCV submission, 14 page excluding references, appearing in proceedings)
2. Uses and Reflection of Computer Vision for Art (Extended abstract, 4 page, excluding references, NOT appearing in proceedings)

New in this edition of the VISART Workshop we introduce a panel session with  renowned experts from Computer Vision and Digital Humanities with the panel members TBA.

The recent explosion in the digitisation of artworks highlights the concrete importance of application in the overlap between CV and art; such as the automatic indexing of databases of paintings and drawings, or automatic tools for the analysis of cultural heritage. Such an encounter, however, also opens the door both to a wider computational understanding of the image beyond photo-geometry, and to a deeper critical engagement with how images are mediated, understood or produced by CV techniques in the `Age of Image-Machines' (T. J. Clark). Submissions to our first track should primarily consist of technical papers, our second track therefore encourages critical essays or extended abstracts from art historians, artists, cultural historians, media theorists and computer scientists.

The purpose of this workshop is to bring together leading researchers in the fields of computer vision and the digital humanities with art and cultural historians and artists, to promote interdisciplinary collaborations, and to expose the hybrid community to cutting-edge techniques and open problems on both sides of this fascinating area of study.

This workshop in conjunction with ECCV 2024, calls for high-quality, previously unpublished, works related to Computer Vision and Cultural History. Submissions for both tracks should conform to the ECCV 2022 proceedings style and will be double-blind peer reviewed by at least three reviewers. However, extended abstracts will not appear in the conference proceedings. Papers must be submitted online through the CMT submission system at:

(Coming Soon)

TOPICS include but are not limited to the follwing:

  • Art History and Computer Vision
  • 3D reconstruction from visual art or historical sites
  • Multi-modal multimedia systems and human machine interaction

  • Visual Question & Answering (VQA) or Captioning for Art
  • Computer Vision for cultural heritage

  • Big-data analysis of art
  • Image and visual representation in art
  • 2D and 3D human pose and gesture estimation in art
  • Multimedia databases and digital libraries for artistic research
  • Interactive 3D media and immersive AR/VR for cultural heritage
  • Approaches for generative art
  • Media content analysis and search

Important Dates


  • Full & Extended Abstract Paper Submission:

    (TBA)

  • Notification of Acceptance:

    (TBA)

  • Camera-Ready Paper Due:

    (TBA)

  • Workshop:

    29th/30th September 2024


Keynotes

Dr. Mathieu Aubry

Bio

Dr. Mathieu Aubry is a tenured researcher in Computer Vision at Êcole des Ponts ParisTech in the LIGM lab (UMR8049). He obtained his PhD at ENS in 2015, co-advised by Josef Sivic (INRIA) and Daniel Cremers (TUM). In 2015, he spent a year working as a postdoc with Alexei Efros in UC Berkeley. He has a leading role in the ANR EnHerit, VHS and EIDA projects and the ERC DISCOVER project on interpretable visual structures discover.

More To Be Announced...

Panel


Dr. Olga Russakovsky

Bio

Dr. Olga Russakovsky is an Associate Professor in the Computer Science Department at Princeton University. Her research is in computer vision, closely integrated with the fields of machine learning, human-computer interaction and fairness, accountability and transparency. In addition to her research, she co-founded and continues to serve on the Board of Directors of the AI4ALL nonprofit dedicated to increasing diversity and inclusion in Artificial Intelligence (AI).

Dr. Mathieu Aubry

Bio

Dr. Mathieu Aubry is a tenured researcher in Computer Vision at Êcole des Ponts ParisTech in the LIGM lab (UMR8049). He obtained his PhD at ENS in 2015, co-advised by Josef Sivic (INRIA) and Daniel Cremers (TUM). In 2015, he spent a year working as a postdoc with Alexei Efros in UC Berkeley. He has a leading role in the ANR EnHerit, VHS and EIDA projects and the ERC DISCOVER project on interpretable visual structures discover.

More To Be Announced...