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Artwork Style Recognition Using Vision Transformers and MLP Mixer
2021
Technologies
Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the
doi:10.3390/technologies10010002
fatcat:2lh7rinolfdatp6z6kpqcz5bea