Abstract
Can artists be recognized from the way they render certain materials, such as fabric, skin, or hair? In this paper, we study this problem with a focus on recognizing works by Rembrandt, Van Dyck, and other Dutch and Flemish artists from the same era. This paper proposes a novel material-based approach based on Swin Transformer and Cascade Mask R-CNN to address artist recognition task. We report the performance on a dataset of 644 images. Additionally, the model’s robustness to image variations is studied.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1771-1777 |
| Number of pages | 7 |
| Journal | IS and T International Symposium on Electronic Imaging Science and Technology |
| Volume | 36 |
| Issue number | 14 |
| DOIs | |
| State | Published - 2024 |
| Event | IS and T International Symposium on Electronic Imaging 2024: Computer Vision and Image Analysis of Art 2024 - San Francisco, United States Duration: Jan 21 2024 → Jan 25 2024 |
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics