Deep learning · Art history · Computer vision
Identify the master behind any painting
The collection
From the Renaissance giants who redefined human expression to the Abstract Expressionists who shattered convention — Art2Artist spans the full arc of Western art history.
Italian Renaissance & Baroque · 15th–17th century
Leonardo da Vinci
1452–1519
Michelangelo
1475–1564
Raphael
1483–1520
Caravaggio
1571–1610
Rembrandt van Rijn
1606–1669
Post-Impressionism & Symbolism · Late 19th century
Edvard Munch
1863–1944
Vincent van Gogh
1853–1890
Gustav Klimt
1862–1918
Paul Cézanne
1839–1906
Impressionism · 19th century
Claude Monet
1840–1926
Edgar Degas
1834–1917
Pierre-Auguste Renoir
1841–1919
Modern & 20th century
Pablo Picasso
1881–1973
Henri Matisse
1869–1954
Salvador Dalí
1904–1989
Joan Miró
1893–1983
Frida Kahlo
1907–1954
Diego Rivera
1886–1957
Jackson Pollock
1912–1956
Mark Rothko
1903–1970
The method
Upload your artwork
Provide any painting — photograph it, screenshot it, or use a URL. The model accepts JPEG, PNG and WebP formats.
Visual analysis
A deep learning model trained on 16,000+ artworks analyzes brushwork, palette, composition, and stylistic signatures.
Artist attribution
The model returns a ranked prediction across all 20 artists, with confidence scores reflecting its certainty.
Explore & learn
Discover the story behind the master, their era, and what makes their visual language instantly recognizable.
Live demo
Upload any painting below and let the model reveal the master behind the canvas.
Drop a painting here
or click to choose a file
Analysing brushwork & palette…
Attributed to
Or open the full Gradio app
Launch on Hugging Face ↗A passion project at the intersection of deep learning and art history — training a model to see what the eye learns over a lifetime of looking at paintings.