WikiArt (formerly known as WikiPaintings) is a visual art wiki, active since 2010.
WikiArt is often used by scientists who study AI. They train AI on WikiArt data trying to discover its ability to recognize, classify, and generate art.
In 2015, computer scientists Babak Saleh and Ahmed Egammal of Rutgers University used images from WikiArt in training an algorithm to look at paintings and detect the works’ genre, style and artist. Later, researchers from Rutgers University, the College of Charleston and Facebook's AI Lab collaborated on a generative adversarial network (GAN), training it on WikiArt data to tell the difference between a piece of art versus a photograph or diagram, and to identify different styles of art. Then, they designed a creative adversarial network (CAN), also trained on WikiArt dataset, to generate new works that does not fit known artistic styles.
In 2016, Chee Seng Chan (Associate Professor at University of Malaya) and his co-researchers trained a convolutional neural network (CNN) on WikiArt datasets and presented their paper "Ceci n’est pas une pipe: A Deep Convolutional Network for Fine-art Paintings Classification". They released ArtGAN to explore the possibilities of AI in its relation to art. In 2017, a new study and improved ArtGAN was published: "Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork".
In 2018, an Edmond de Belamy portrait produced by a GAN was sold for $432,500 at a Christie's auction. The algorithm was trained on a set of 15,000 portraits from WikiArt, spanning the 14th to the 19th century.
In 2019, Eva Cetinic, a researcher at the Rudjer Boskovic Institute in Croatia, and her colleagues, used images from WikiArt in training machine-learning algorithms to explore the relationship between the aesthetics, sentimental value, and memorability of fine art.
In 2020, Panos Achlioptas, a researcher at Stanford University and his co-researchers collected 439,121 affective annotations involving emotional reactions and written explanations of those, for 81 thousand artworks of WikiArt. Their study involved 6,377 human annotators and it resulted in the first neural-based speaker model that showed non-trivial Turing test performance in emotion-explanation tasks.
- "Financial Report 2012 Q1". WikiPaintings blog. 6 April 2012. Archived from the original on 14 June 2012. Retrieved 18 August 2023.
Unfortunately, our country (Ukraine) [...]
- "Forbes: Украинцы создали первую сетевую энциклопедию визуального искусства" [Forbes: Ukrainians have created the first online encyclopaedia of visual art]. Korrespondent.net (in Russian). 6 July 2012. Retrieved 18 August 2023.
- "WikiArt visual encyclopaedia blocked in Russia". Novaya Gazeta Europe. 16 August 2008. Retrieved 18 August 2023.
- Fessenden, Marissa (13 May 2015). "Computers Are Learning About Art Faster than Art Historians". Smithsonian Magazine. Retrieved 18 August 2023.
- Daley, Jason (3 July 2017). "AI Project Produces New Styles of Art". Smithsonian Magazine. Retrieved 18 August 2023.
- Cascone, Sarah (11 July 2017). "AI-Generated Art Now Looks More Human Than Work at Art Basel, Study Says". Artnet News. Retrieved 18 August 2023.
- Tan, Wei Ren; Chan, Chee Seng; Aguirre, Hernan E.; Tanaka, Kiyoshi (September 2016). "Ceci n'est pas une pipe: A deep convolutional network for fine-art paintings classification" (PDF). 2016 IEEE International Conference on Image Processing (ICIP). pp. 3703–3707. doi:10.1109/ICIP.2016.7533051. ISBN 978-1-4673-9961-6. S2CID 18920693.
- Wei Ren Tan; Chee Seng Chan; Aguirre, Hernan; Tanaka, Kiyoshi (2017). "Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork". arXiv:1708.09533 [cs.CV].
- Nugent, Ciara (20 August 2018). "The Painter Behind These Artworks Is an AI Program. Do They Still Count as Art?". Time. Retrieved 18 August 2023.
- Hampson, Michelle (14 June 2019). "What Can AI Tell Us About Fine Art?". IEEE Spectrum. Retrieved 18 August 2023.
- Achlioptas, Panos; Ovsjanikov, Maks; Haydarov, Kilichbek; Elhoseiny, Mohamed; Guibas, Leonidas (2021). "ArtEmis: Affective Language for Visual Art". arXiv:2101.07396 [cs.CV].