Webly-supervised Zero-shot Learning for Artwork Instance Recognition

•We extend our previous work on webly-supervised learning for artwork instance recognition on the NoisyArt dataset.•Experiments show that normalization of visual representations boosts robustness to noise in webly-supervised learning.•Our results on webly-supervised instance recognition significantly outperform earlier techniques.•Zero-shot learning experiments show that unseen instances can be recognized even when using webly-supervised training data.