Art Recognition

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Art Recognition is a technology company headquartered in Adliswil, within the Zurich metropolitan area, Switzerland. Specializing in the application of artificial intelligence (AI) for the purposes of art authentication and the detection of art forgeries, Art Recognition integrates advanced algorithms and computer vision technology. The company's operations extend globally, with a primary aim to increase transparency and security in the art market.

Contents

History

Art Recognition was established in 2019 by Dr. Carina Popovici and Christiane Hoppe-Oehl. The foundation of the company was driven by the long-standing challenge in the art world of authenticating paintings, a process traditionally reliant on expert judgment, historical research, and scientific analysis. Recognizing the limitations of existing methods, the co-founders were motivated by technological advancements in digital imaging and pattern recognition algorithms in the field of art.

These technological advancements, particularly in the realm of high-resolution digital imagery, enable a more detailed examination of artworks. [1] By analyzing brushstrokes, signature patterns, and other distinct characteristics, and comparing them with known works by the same artist, digital tools offer a new dimension in authentication. Popovici and Hoppe-Oehl aimed to develop an advanced algorithm that could further assist experts by identifying stylistic elements and patterns unique to individual artists, thus aiding in the art authentication process.

Technology and methodology

The AI Report includes an AI-determined authenticity probability, analytical heatmaps, brushstroke visualizations, and outlines the methodology and historical context. REPORT example Cezanne Boy in a red vest ENGLISH. ENCRYPTED.pdf
The AI Report includes an AI-determined authenticity probability, analytical heatmaps, brushstroke visualizations, and outlines the methodology and historical context.

Art Recognition employs a combination of machine learning techniques, computer vision algorithms, and deep neural networks to assess the authenticity of artworks. [2] The AI algorithm analyzes various visual characteristics, such as brushstrokes, color palette, texture, and composition, to identify patterns and similarities with known authentic artworks.

The company's technology undergoes a process of data collection, dataset preparation, and training. In the initial phase, datasets are compiled, and data selection is supervised by art historians to ensure the inclusion of genuine artworks by specific artists. This approach aims to avoid including artworks that may have been partially completed by apprentices or contain mixed authorship.

Upon the preparation of datasets, a segment of the image set is used for training the AI algorithm, while the remaining images are set aside for testing. This phase aims to ensure the algorithm's proficiency in distinguishing authentic artworks from forgeries. Post-training, the algorithm undergoes evaluation with the test data, assessing its accuracy and efficacy in authenticating artworks.

After the testing phase, the AI algorithm is applied to analyze new images, including submissions from clients. Additionally, the algorithm is designed to identify artworks generated by generative AI, mimicking the style of renowned artists. This capability equips the algorithm to withstand adversarial attacks, enhancing its reliability in differentiating between authentic and artificially generated fake art pieces. [3]

Academic partnerships and grants

Art Recognition's collaboration with Tilburg University in The Netherlands has resulted in the acquisition of a research grant from Eurostars,Eureka (organisation) the Eureka's flagship small and medium-sized enterprises (SME) funding program. In addition, the company has formed a partnership with the University of Liverpool in the United Kingdom, which has been supported by the Science and Technology Facilities Council (STFC) Impact Acceleration Award. Furthermore, Art Recognition has established a relationship with Innosuisse, a Swiss innovation agency, [4] to expand its research and development initiatives.

Recognition and impact

Art Recognition's AI algorithm has received attention from various media outlets and industry events. The company was featured on the front page of The Wall Street Journal [5] for its involvement in the authentication case of the Flaget Madonna, believed to have been partly painted by Raphael.

A broadcast by the Swiss public television SRF showcased how the algorithm can be used to detect art forgeries with high accuracy. [6] Additionally, the company's work was featured in a TEDx talk discussing the use of AI in art authentication.

Debates and discussions

The technology developed by Art Recognition has been recognized for its role in providing a technology-based art authentication solution, compared to traditional methods. This advancement is seen as significant in the field of art verification, offering a modern approach to a historically complex process. [7]

The use of AI in art authentication, as pioneered by Art Recognition, has become a topic of professional discourse. Notably, this subject was the focus of a debate on Radio Télévision Suisse, where experts deliberated over the capabilities and limitations of AI in identifying art forgeries. Such discussions highlight the evolving landscape of art authentication in the age of digital technology. [8]

Despite the advancements in AI-driven art authentication, the field continues to face unique challenges, particularly regarding the acceptance of such technologies. Experts in the field stress the necessity of using AI as a complementary tool alongside traditional methods, rather than as a stand-alone or definitive solution for authenticating art. [9]

Controversial cases

Art Recognition's AI algorithm has been applied to several high-profile and controversial artworks, sparking significant interest and debate in the art world.

  1. Samson and Delilah at the National Gallery in London: The National Gallery's "Samson and Delilah", traditionally attributed to the artist Rubens, has also been examined using Art Recognition's AI, which has assessed the painting as non-authentic. This analysis contributed to ongoing scholarly discussions regarding the work's authenticity. [10]
  2. De Brecy Tondo Madonna. A research team from Bradford University and Nottingham University initially attributed the painting to Raphael, employing an AI face recognition software, [11] while the AI developed at Art Recognition returned a negative result. [12] As the face recognition method proved inadequate for art authentication, [13] the Bradford group developed a new technology more akin to the approach used by Art Recognition. Notably, a crucial difference emerged in the datasets used to train the respective AI systems. While the Bradford group's AI was trained using 49 images, Art Recognition utilized a substantially larger dataset of over 100 images. This difference in the size and composition of the training datasets underscored the significant impact that data selection has on the outcomes of AI-driven art analysis. [14]
  3. Lucian Freud Painting Controversy: Featured in The New Yorker, a painting attributed to Lucian Freud became a subject of dispute. Art Recognition's AI analysis played a pivotal role in examining the painting's authenticity, contributing to the broader discussion about the challenges in verifying modern artworks. [15]
  4. Titian at Kunsthaus Zürich: A painting attributed to Titian, housed at Kunsthaus Zürich, has been a topic of debate among art experts. The application of Art Recognition's technology offered a new perspective, utilizing AI to analyze the painting's stylistic elements in comparison with authenticated works of Titian. Following this debate, Kunsthaus Zürich has announced plans to initiate a comprehensive project aimed at resolving the authenticity questions surrounding the painting. This project is set to involve collaboration with scientists and technology companies, leveraging a multidisciplinary approach to authenticate the artwork. [16]

In each of these instances, Art Recognition's involvement has provided additional perspectives through AI analysis while contributing to broader conversations about the role of technology in art authentication. These cases demonstrate the evolving nature of art verification, where traditional methods are being supplemented, and sometimes challenged, by new technological approaches. However, they also underline the ongoing debates about the acceptance of AI in the field of art history, especially in the authentication of works by renowned artists.

Related Research Articles

A signature is a handwritten depiction of someone's name, nickname, or even a simple "X" or other mark that a person writes on documents as a proof of identity and intent. The writer of a signature is a signatory or signer. Similar to a handwritten signature, a signature work describes the work as readily identifying its creator. A signature may be confused with an autograph, which is chiefly an artistic signature. This can lead to confusion when people have both an autograph and signature and as such some people in the public eye keep their signatures private whilst fully publishing their autograph.

<span class="mw-page-title-main">Authentication</span> Act of proving an assertion

Authentication is the act of proving an assertion, such as the identity of a computer system user. In contrast with identification, the act of indicating a person or thing's identity, authentication is the process of verifying that identity. It might involve validating personal identity documents, verifying the authenticity of a website with a digital certificate, determining the age of an artifact by carbon dating, or ensuring that a product or document is not counterfeit.

<span class="mw-page-title-main">Digital art</span> Collective term for art that is generated digitally with a computer

Digital art refers to any artistic work or practice that uses digital technology as part of the creative or presentation process. It can also refer to computational art that uses and engages with digital media.

Computer art is art in which computers play a role in the production or display of the artwork. Such art can be an image, sound, animation, video, CD-ROM, DVD-ROM, video game, website, algorithm, performance or gallery installation. Many traditional disciplines are now integrating digital technologies and, as a result, the lines between traditional works of art and new media works created using computers has been blurred. For instance, an artist may combine traditional painting with algorithm art and other digital techniques. As a result, defining computer art by its end product can thus be difficult. Computer art is bound to change over time since changes in technology and software directly affect what is possible.

<span class="mw-page-title-main">Art forgery</span> Creation and trade of falsely credited art

Art forgery is the creation and sale of works of art which are falsely credited to other, usually more famous artists. Art forgery can be extremely lucrative, but modern dating and analysis techniques have made the identification of forged artwork much simpler.

<i>Bacchus and Ariadne</i> Painting by Titian

Bacchus and Ariadne (1522–1523) is an oil painting by Titian. It is one of a cycle of paintings on mythological subjects produced for Alfonso I d'Este, Duke of Ferrara, for the Camerino d'Alabastro – a private room in his palazzo in Ferrara decorated with paintings based on classical texts. An advance payment was given to Raphael, who originally held the commission for the subject of a Triumph of Bacchus.

<span class="mw-page-title-main">Algorithmic art</span> Art genre

Algorithmic art or algorithm art is art, mostly visual art, in which the design is generated by an algorithm. Algorithmic artists are sometimes called algorists.

<i>Samson and Delilah</i> (Rubens) Painting by Peter Paul Rubens

Samson and Delilah is a painting long attributed to the Flemish Baroque artist Peter Paul Rubens (1577–1640) in the National Gallery, London. It dates from about 1609 to 1610.

Anthony Gene Tetro, known as Tony Tetro, is an art forger known for his perfectionism in copies of artwork produced in the 1970s and 1980s. Tetro never received formal art lessons, but learned from books, by painting and experimentation. Over three decades, Tetro forged works by Rembrandt, Joan Miró, Marc Chagall, Salvador Dalí and Norman Rockwell and others. Tetro's paintings and lithographs, known for their perfectionism, were sold by art dealers and auction houses as legitimate works and hang in museums, galleries around the world. He was caught after Hiro Yamagata found a forgery of his own work for sale in a gallery.

Music and artificial intelligence is the development of music software programs which use AI to generate music. As with applications in other fields, AI in music also simulates mental tasks. A prominent feature is the capability of an AI algorithm to learn based on past data, such as in computer accompaniment technology, wherein the AI is capable of listening to a human performer and performing accompaniment. Artificial intelligence also drives interactive composition technology, wherein a computer composes music in response to a live performance. There are other AI applications in music that cover not only music composition, production, and performance but also how music is marketed and consumed. Several music player programs have also been developed to use voice recognition and natural language processing technology for music voice control. Current research includes the application of AI in music composition, performance, theory and digital sound processing.

Hany Farid is an American university professor who specializes in the analysis of digital images and the detection of digitally manipulated images such as deepfakes. Farid served as Dean and Head of School for the UC Berkeley School of Information. In addition to teaching, writing, and conducting research, Farid acts as a consultant for non-profits, government agencies, and news organizations. He is the author of the book Photo Forensics (2016).

<span class="mw-page-title-main">Authenticity in art</span>

Authenticity in art is manifest in the different ways that a work of art, or an artistic performance, can be considered authentic. The initial distinction is between nominal authenticity and expressive authenticity. In the first sense, nominal authenticity is the correct identification of the author of a work of art; of how closely an actor or an actress interprets a role in a stageplay as written by the playwright; of how well a musician's performance of an artistic composition corresponds to the composer's intention; and how closely an objet d’art conforms to the artistic traditions of its genre. In the second sense, expressive authenticity is how much the work of art possesses inherent authority of and about its subject, and how much of the artist's intent is in the work of art.

<i>Lincoln in Dalivision</i> Painting by Salvador Dalí

Lincoln in Dalivision is a 1977 original limited edition lithograph created by Salvador Dalí. It is often considered one of the most counterfeited Dalí lithographs. Dalí authentication experts who have noted the counterfeiting issue with this work include Albert Field, Frank Hunter, Robert Descharnes and Bernard Ewell. Lee Catterall comments in his book The Great Dalí Art Fraud & other deceptions, "The painting most commonly reproduced for such fraudulent purposes was Lincoln in Dalivision, 'prints' of which Los Angeles art appraiser Dena Hall testified in the Hawaii trial have become as commonplace as 'pancakes at the pancake house.'"

Wolfgang Beltracchi is a German art forger and visual artist who has admitted to forging hundreds of paintings in an international art scam netting millions of euros. Beltracchi, together with his wife Helene, sold forgeries of alleged works by famous artists, including Max Ernst, Heinrich Campendonk, Fernand Léger, and Kees van Dongen. Though he was found guilty for forging 14 works of art that sold for a combined $45m (£28.6m), he claims to have faked "about 50" artists. The total estimated profits Beltracchi made from his forgeries surpasses $100m.

<span class="mw-page-title-main">WikiArt</span> User-generated website displaying artworks

WikiArt is a visual art wiki, active since 2010.

<span class="mw-page-title-main">Artificial intelligence art</span> Machine application of knowledge of human aesthetic expressions

Artificial intelligence art is any visual artwork created through the use of artificial intelligence (AI) programs such as text-to-image models. AI art began to gain popularity in the mid- to late-20th century through the boom of artificial intelligence.

<span class="mw-page-title-main">Megvii</span> Chinese technology company

Megvii is a Chinese technology company that designs image recognition and deep-learning software. Based in Beijing, the company develops artificial intelligence (AI) technology for businesses and for the public sector.

Deepfake pornography, or simply fake pornography, is a type of synthetic pornography that is created via altering already-existing pornographic material by applying deepfake technology to the faces of the actors. The use of deepfake porn has sparked controversy because it involves the making and sharing of realistic videos featuring non-consenting individuals, typically female celebrities, and is sometimes used for revenge porn. Efforts are being made to combat these ethical concerns through legislation and technology-based solutions.

<span class="mw-page-title-main">DALL-E</span> Image-generating deep-learning model

DALL·E, DALL·E 2, and DALL·E 3 are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions, called "prompts."

Fine art authentication is a process that ensures the integrity of artworks, preserves cultural heritage, and maintains trust in the art market. By combining traditional methods, scientific advancements, and emerging AI and Blockchain technologies, art authentication can offer accurate attributions and protect the artistic legacy for future generations. It consists of proving the authenticity of an artwork and its attribution to a specific artist. This process involves determining the origin, authorship, and historical significance of a piece of art. The proliferation of art forgeries and the increased skill of the forgers who are aware of what scientific analysis reveals requires a rigorous approach to fine art authentication.

References

  1. "New tools are making it easier to authenticate paintings". The Economist. ISSN   0013-0613 . Retrieved 2024-02-10.
  2. Schaerf, Ludovica; Popovici, Carina; Postma, Eric (2023-07-10), Art Authentication with Vision Transformers, arXiv: 2307.03039
  3. "2312.14998 - Synthetic images aid the recognition of human-made art forgeries". www.emergentmind.com. Retrieved 2024-02-10.
  4. "Innosuisse Discover 2021 - Recognising art forgeries from a photo". InnoSuisse. Retrieved 2024-02-10.
  5. "Is This a Real Raphael Painting? AI Says Yes, But Humans Aren't So Sure". WSJ. Retrieved 2024-02-10.
  6. "Die Idee - Mit einem Algorithmus Kunstfälschungen erkennen". Schweizer Radio und Fernsehen (SRF) (in German). 2020-10-23. Retrieved 2024-02-10.
  7. Müller, André (2020-01-19). "Art Recognition: Carina Popovici legt Kunstfälschern das Handwerk". Neue Zürcher Zeitung (in Swiss High German). ISSN   0376-6829 . Retrieved 2024-02-10.
  8. "L'intelligence artificielle peut-elle détecter les faux dans l'art?". rts.ch (in French). 2021-12-19. Retrieved 2023-06-23.
  9. "AI Companies Are Authenticating Old Master Paintings, But the Art World is Skeptical". Observer. 2023-03-01. Retrieved 2024-02-10.
  10. Alberge, Dalya (2021-09-26). "Was famed Samson and Delilah really painted by Rubens? No, says AI". The Observer. ISSN   0029-7712 . Retrieved 2024-02-10.
  11. Khomami, Nadia; Arts, Nadia Khomami; correspondent, culture (2023-07-14). "Painting 'undoubtedly' by Raphael to go on display in Bradford". The Guardian. ISSN   0261-3077 . Retrieved 2024-02-10.
  12. https://www.theartnewspaper.com/2023/09/11/a-question-of-attribution-how-useful-can-ai-tools-be
  13. Popovici, Carina (2023-10-24). "Two A.I. Models Produced Different Results When Authenticating a Raphael Painting. Here's Why That Doesn't Undermine the Tool's Potential". Artnet News. Retrieved 2024-02-10.
  14. Harris, Gareth. "AI meets Old Masters in the fight to authenticate paintings". The Financial TImes.
  15. Knight, Sam (2022-09-19). "The Case of the Disputed Lucian Freud". The New Yorker. ISSN   0028-792X . Retrieved 2024-02-10.
  16. Dafoe, Taylor (2023-03-28). "A Zurich Museum Found Out It May Have Acquired a Fake Titian. So Why Did It Buy Another Painting That Looks Just Like It?". Artnet News. Retrieved 2024-02-10.

[1]

  1. Harris, Gareth (2023-10-24). "A question of attribution: just how useful can AI tools be?". The Art Newspaper.