Image Colorization By Capsule Networks
| Autor: | Gokhan Ozbulak |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Contextual image classification Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Image and Video Processing (eess.IV) Feature extraction Computer Science - Computer Vision and Pattern Recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Pattern recognition 02 engineering and technology Electrical Engineering and Systems Science - Image and Video Processing 010501 environmental sciences Color space 01 natural sciences Grayscale Feature (computer vision) Margin (machine learning) FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Segmentation Artificial intelligence business 0105 earth and related environmental sciences |
| Zdroj: | CVPR Workshops |
| Popis: | In this paper, a simple topology of Capsule Network (CapsNet) is investigated for the problem of image colorization. The generative and segmentation capabilities of the original CapsNet topology, which is proposed for image classification problem, is leveraged for the colorization of the images by modifying the network as follows:1) The original CapsNet model is adapted to map the grayscale input to the output in the CIE Lab colorspace, 2) The feature detector part of the model is updated by using deeper feature layers inherited from VGG-19 pre-trained model with weights in order to transfer low-level image representation capability to this model, 3) The margin loss function is modified as Mean Squared Error (MSE) loss to minimize the image-to-imagemapping. The resulting CapsNet model is named as Colorizer Capsule Network (ColorCapsNet).The performance of the ColorCapsNet is evaluated on the DIV2K dataset and promising results are obtained to investigate Capsule Networks further for image colorization problem. Comment: Accepted to New Trends in Image Restoration and Enhancement(NTIRE) Workshop at CVPR 2019 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|