The #dhnord colloquium brings together the digital humanities community every year at the Maison Européenne des Sciences de l'Homme et de la Société - MESHS in Lille. The theme chosen for 2020 considers computational approaches to images in the history and theory of the arts. This conference will bring together for the first time in France the leading specialists in artificial intelligence applied to the arts. The history of arts and culture, as well as aesthetics, have greatly benefited in recent years from the results of heritage digitization campaigns. Since 2013, digital art history has experienced unprecedented growth, particularly in the Anglo-Saxon spheres and in Europe (Joyeux-Prunel, Drucker 2013, Zorich 2012). While the analysis of texts has long been favored by the digital humanities, it is now becoming possible to carry out computational analyses on the very matter of images, or even on 3D objects, which constitutes a major turning point. This colloquium will explore how computational methods are renewing traditional questions of art history, aesthetics and visual culture (creative process, style, form, attribution, iconology, circulation of works, etc.) and raising new research questions for our disciplines (visual arts, architecture, theatre, cinema, photography, etc.) at a time when new tools are becoming available to researchers.
Papers will address the following topics: uses of artificial intelligence (especially deep learning and machine learning) applied to image corpora, data construction, and processing issues, epistemological questions related to the selection of training corpora and the use of tools, historical evolution of the field, renewal of research questions, availability of corpora, reproducibility of research and sharing of models. The invitation to foreign speakers and the need to exchange our work in an international context implies that the language used for oral communications will be English.
Due to the sanitary crisis provoked by COVID-19, DHnord2020 will take place online, with asynchronous and videoconference components. Recordings of our participants will be annotated with MemoRekall, which alongside annotations of already existing conferences, will constitute a videography that will become a reference for the study of computational approaches to art history. This videography will remain online well past November 2020, and thus, DHnord2020 will not be as ephemeral as other conferences.
Additionally, during the original dates of the conference; November 18-20, we will hold round tables discussing the papers and the impact of these new methods in the field of art history more generally.
There will also be poster presentations, and a call for proposals will soon be available.
Finally, a collective book resulting from the conference will be published by the Presses Universitaires du Septentrion and will be available in Open Access. We encourage authors to publish the datasets and the computer code jointly.
Original Presentations
(Pre-recorded talks are available, click on the link to see them)
- Béatrice Joyeux-Prunel, Université de Genève, “Tracking the Circulation of Images Digitally. From Artistic Cartography to the Study of Visual Contagions”
- Stefaan Van Liefferinge, Gabriel S. Rodriguez and Lisa Peck, Columbia University, “The Art Historical Image Collection at Columbia University: Automating Research on its Construction and Creators”
- Pierre-Carl Langlais, Université Paul-Valéry Montpellier 3 / Sorbonne Université, “Viral Stereotypes: Analyzing Historical Circulations of Media Images through Deep Learning”
- Isabella di Lenardo, École polytechnique fédérale de Lausanne, “Paintings by AI. Large-scale search for visual similarities”
Understanding Images through AI : Modalization and Operationalizing
- Nicolas Gonthier, Yann Gousseau, and Saïd Ladjal, Télécom Paris, “Transfer Learning and Visualization of Neural Networks for Artistic Images"
- Peter Bell, University of Erlangen-Nürnberg (FAU), “Angelic movement. Exploring and Understanding Art, Iconography and Composition with Machine Learning”
- Timothy R. Tangherlini, University of California, Berkeley; Peter Broadwell, Stanford University “ [I want to dance]: Comparative K-Pop Choreography Analysis through Deep-Learning Pose Estimation”
- Matthew Lincoln, Carnegie Mellon University, “Yet another digital surrogate? Computer vision and the future of collections management systems”
From Artificial Intelligence to Aesthetic Intelligence
- Leonardo Impett, University of Durham, "The Image-Theories behind Computer Vision”
- Johanna Drucker, University of California, Los Angeles, “Image Mis-recognition: Augmentation, Automation, and Aesthetic Intelligence”
- Dominique Cardon, Sciences Po, “A machine that Reads Images: a Social and Technical History of Artificial Intelligence in Computer Vision”
AI Aesthetics to Cultural Analytics
- Emily L. Spratt, Columbia University, “The Augmented Dataset: Artistic Appropriations of GANs and their Bearings on Ethical Considerations of AI”
Presentations of Digital Tools
(Pre-recorded talks are available, click on the link to see them)
- Leonardo Impett, University of Durham, “ImageGraph: a visual programming language for the Visual Digital Humanities”
- Lauren Tilton and Taylor Arnold, University of Richmond, “Distant Viewing Toolkit: Software for analysing digital culture”
Live Round Tables
Tuesday 17 November
1. From One Image to Another: Circulations, Transmissions, and Intervals
D’une image à l’autre : circulations, transmissions et intervalles
- Moderator: Nuria Rodríguez Ortega, University of Málaga
- Béatrice Joyeux-Prunel, University of Geneva
- Stefaan Van Liefferinge, Columbia University
- Isabella di Lenardo, École polytechnique fédérale de Lausanne
- Pierre-Carl Langlais, Université Paul-Valéry Montpellier 3 and Sorbonne Université
Wednesday 18 November
2. Understanding Images through Machine Learning and Deep Learning
Comprendre les images avec le machine learning et le deep learning
- Mod: Taylor Arnold, University of Richmond
- Nicolas Gonthier, Télécom Paris
- Peter Bell, University of Erlangen-Nürnberg (FAU)
- Timothy R. Tangherlini, University of California, Berkeley
- Matthew Lincoln, Carnegie Mellon University
Thursday 19 November
3. From Artificial Intelligence to Aesthetic Intelligence
De l’intelligence artificielle à l’intelligence esthétique
- Mod: Clarisse Bardiot, Université Polytechnique Hauts-de-France & Emmanuel Château-Dutier, Université de Montréal
- Leonardo Impett, University of Durham
- Dominique Cardon, Sciences Po
- Johanna Drucker, University of California, Los Angeles
Friday 20 November
4. Cultural Analytics : a dialogue between Lev Manovich and Emily L. Spratt, moderated by Everardo Reyes
“Cultural Analytics” : une dialogue entre Lev Manovich et Emily L. Spratt, modéré par Everardo Reyes
- Mod: Everardo Reyes, Université Paris 8
- Lev Manovich, City University of New York
- Emily L. Spratt, Columbia University
Friday 20 November
5. The Stakes of AI for Large Collections of Images and Research Infrastructures
Enjeux de l’IA pour les grandes collections d’images et les infrastructures de recherche
- Mod: Clarisse Bardiot, Université Polytechnique Hauts-de-France & Emmanuel Château-Dutier, Université de Montréal
- Emmanuelle Bermès, Bibliothèque Nationale de France
- Nanne van Noord, University of Amsterdam and Netherlands Institute for Sound and Vision
- Antoine Courtin, Institut National d’Histoire de l’Art
- Emily Pugh, Getty Research Institute
- Tristan Weddigen, Biblioteca Hertziana Max-Planck-Institute and University of Zurich
- Dario Negueruela del Castillo, Max Planck Society and University of Zurich
Ateliers pratiques
en français uniquement / french language only
Mardi, 17 novembre : Jean-Philippe Moreux, l’expert scientifique de Gallica à la Bibliothèque nationale de France, “Fouille d'images patrimoniales : expérimentations, outils.”
Mercredi, 18 novembre : Régis Robineau, coordinateur technique de Biblissima and Johann Holland, TGIR Huma-Num, “Adopter et utiliser les standards IIIF pour vos corpus d'images numériques.”
Mercredi, 18 novembre : Tom Monnier, doctorant à Imagine - École des Ponts ParisTech “Extraction automatique d’illustrations et lignes de texte au sein de documents IIIF.”
[Live] Day by Day schedule
Atelier pratique (uniquement en français / french language only)
13h - 16h (CET Paris)
7 am - 10 am (EDT Montréal)
4 am - 7 am (PDT Los Angeles)
“Fouille d'images patrimoniales : expérimentations, outils.”
Jean-Philippe Moreux, l’expert scientifique de Gallica à la Bibliothèque nationale de France,
17h - 18h30 (CET Paris)
11 am - 12.30 pm (EDT Montréal)
8 am - 9.30 am (PDT Los Angeles)
From One Image to Another: Circulations, Transmissions, and Intervals
D’une image à l’autre : circulations, transmissions et intervalles
- Moderator: Nuria Rodríguez Ortega, University of Málaga
- Béatrice Joyeux-Prunel, University of Geneva
- Stefaan Van Liefferinge, Columbia University
- Isabella di Lenardo, École polytechnique fédérale de Lausanne
- Pierre-Carl Langlais, Université Paul-Valéry Montpellier 3 and Sorbonne Université
Ateliers pratiques (uniquement en français / french language only )
10h - 12h (CET Paris)
4 am - 6 am (EDT Montréal)
1 am - 3 am (PDT Los Angeles)
“Adopter et utiliser les standards IIIF pour vos corpus d'images numériques.”
Régis Robineau, coordinateur technique de Biblissima and Johann Holland, TGIR Huma-Num
13h - 15h (CET Paris)
7 am - 9 am (EDT Montréal)
4 am - 6 am (PDT Los Angeles)
“Extraction automatique d’illustrations et lignes de texte au sein de documents IIIF.”
Tom Monnier, doctorant à Imagine - École des Ponts ParisTech
17h - 18h30 (CET Paris)
11 am - 12.30 pm (EDT Montréal)
8 am - 9.30 am (PDT Los Angeles)
Understanding Images through Machine Learning and Deep Learning
Comprendre les images avec le machine learning et le deep learning
- Mod: Taylor Arnold, University of Richmond
- Nicolas Gonthier, Télécom Paris
- Peter Bell, University of Erlangen-Nürnberg (FAU)
- Timothy R. Tangherlini, University of California, Berkeley
- Matthew Lincoln, Carnegie Mellon University
17h - 18h30 (CET Paris)
11 am - 12.30 pm (EDT Montréal)
8 am - 9.30 am (PDT Los Angeles)
From Artificial Intelligence to Aesthetic Intelligence
De l’intelligence artificielle à l’intelligence esthétique
- Mod: Clarisse Bardiot, Université Polytechnique Hauts-de-France & Emmanuel Château-Dutier, Université de Montréal
- Leonardo Impett, University of Durham
- Dominique Cardon, Sciences Po
- Johanna Drucker, University of California, Los Angeles
12h - 13h30 (CET Paris)
6 am - 7.30 am (EDT Montréal)
3 am - 4.30 am (PDT Los Angeles)
4. Cultural Analytics : a dialogue between Lev Manovich and Emily L. Spratt, moderated by Everardo Reyes
“Cultural Analytics” : une dialogue entre Lev Manovich et Emily L. Spratt, modéré par Everardo Reyes
- Mod: Everardo Reyes, Université Paris 8
- Lev Manovich, City University of New York
- Emily L. Spratt, Columbia University
17h - 18h30 (CET Paris)
11 am - 12.30 pm (EDT Montréal)
8 am - 9.30 am (PDT Los Angeles)
5. The Stakes of AI for Large Collections of Images and Research Infrastructures
Enjeux de l’IA pour pour les grandes collections d’images et les infrastructures de recherche
- Mod: Clarisse Bardiot, Université Polytechnique Hauts-de-France & Emmanuel Château-Dutier, Université de Montréal
- Emmanuelle Bermès, Bibliothèque Nationale de France
- Nanne van Noord, University of Amsterdam and Netherlands Institute for Sound and Vision
- Antoine Courtin, Institut National d’Histoire de l’Art
- Emily Pugh, Getty Research Institute
- Tristan Weddigen, Biblioteca Hertziana Max-Planck-Institute and University of Zurich
- Dario Negueruela del Castillo, Max Planck Society and University of Zurich
"Training the Archive: A research project with the aim to structure information and data of museum collections and make them accessible to curators in an exploratory way" Dominik Bönisch, Ludwig Forum for International Art Aachen
"Les artistes contemporains et leurs œuvres sur les réseaux sociaux : Une nouvelle source pour l’histoire de l’art ?" Adrien Jeanrenaud, École nationale des chartes
"Des images au texte : LECTAUREP, un projet de reconnaissance automatique d'écriture" Alix Chagué, Lucas Terriel, and Laurent Romary, Inria Project ALMAnaCH
Organizers
Chairs : Clarisse Bardiot and Emmanuel Château-Dutier
Project Manager & Editing of MemoRekall Capsules: Edward J. Gray
Scientific Committee :
- Elise Baillieul (ULille)
- Clarisse Bardiot (UPHF, MESHS)
- Emmanuel Château-Dutier (Université de Montréal, CRIHN)
- Antoine Courtin (INHA)
- Océane Delleaux (ULille)
- Béatrice Joyeux-Prunel (University of Geneva)
- Nicolas Hervé (INA)
- Kristine Tanton (Université de Montréal, CRIHN)
- Nicolas Thély (University of Rennes, MSHB)
Partners
- CNRS
- CRIHN (Montreal)
- MESRI
- Région Hauts-de-France
- Université de Lille
- Université d'Artois
- Université du Littoral Côte d'Opale
- Université Polytechnique Hauts-de-France
- Université Catholique de Lille
- Université de Picardie Jules Vernes
Bibliography
- Arnold, Taylor et Lauren Tilton. s. d. « Distant Viewing: Analyzing Large Visual Corpora ». Digital Scholarship in the Humanities. https://doi.org/10.1093/digitalsh/fqz013
- Drucker, Johanna. 2013. « Is There a “Digital” Art History? » Visual Resources 29 (1-2, Digital Art History). Routledge : 5-13. https://doi.org/10.1080/01973762.2013.761106.
- Ellis, Margaret Holben et C. Richard Johnson Jr. 2019. « Computational Connoisseurship: Enhanced Examination Using Automated Image Analysis ». Visual Resources 35 (1-2, Digital Art History). Routledge : 125-140. https://doi.org/10.1080/01973762.2019.1556886.
- Moretti, Franco et Leonardo Impett. 2017. « Totentanz. Operationalizing Aby Warburg’s Pathosformeln. Pamphlets 16 ». Literary Lab, Stanford.https://litlab.stanford.edu/LiteraryLabPamphlet16.pdf.
- Joyeux-Prunel, Béatrice. 2010. L’art et la mesure : histoire de l’art et méthodes quantitatives. Actes de la recherche à l’Ens 5. Paris : Éditions Rue d’Ulm ; Presses de l’École normale supérieure.
- Klinke, Harald et Liska Surkemper, éds. 2016. Visualising big image data. International Journal of Digital Art History.
- Manovich, Lev. 2012. « How to Compare One Million Images? » Dans Understanding Digital Humanities, édité par David M. Berry, 249-278. London : Palgrave Macmillan UK. https://doi.org/10.1057/9780230371934_14.
- Rodríguez-Ortega, Nuria. 2020. « Image processing and computer vision in the field of digital art history. » Dans The Routledge Companion to Digital Humanities and Art History. Brown, Kathryn, éd. Routledge Art History and Visual Studies Companions. New York : Routledge.
- Seguin, Benoit. 2018. « The Replica Project: Building a Visual Search Engine for Art Historians ». XRDS 24 (3) : 24–29. https://doi.org/10.1145/3186653.
- Shen, Xi, Alexei A. Efros et Mathieu Aubry. 2019. « Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning ». arXiv:1903.02678 [cs], mars. http://arxiv.org/abs/1903.02678.
- Vane, Olivia. 2019. Timeline Design For Visualising Cultural Heritage Data. PhD Thesis, Innovation Design Engineering, Londres : Royal College of Art.
- Wevers, Melvin et Thomas Smits. s. d. « The Visual Digital Turn: Using Neural Networks to Study Historical Images ». Digital Scholarship in the Humanities. https://doi.org/10.1093/llc/fqy085.
#dhnord is organized in partnership with CRIHN and the support of the French state and "Conseil Régional des Hauts-de-France" as part of CPER ISI-MESHS
URI/Permalink: https://www.meshs.fr/page/dhnord2020en
