Learning Representations for Automatic Colorization
Published:
image pass through VGG16
- concat features in all conv layers
- train a fc layer for hue and chroma histograms
- loss: bin the Lab axes by evenly spaced Gaussian quantiles
- apply KL loss
- findings
- networks trained by colorization generalize well to other tasks