Semantic Segmentation Alternative Technique: Segmentation Domain Generation
- Resource Type
- Working Paper
- Authors
- Rogoz, Ana-Cristina; Muntean, Radu; Cobeli, Stefan
- Source
- Subject
- Computer Science - Computer Vision and Pattern Recognition
Computer Science - Machine Learning
Electrical Engineering and Systems Science - Image and Video Processing
- Language
Detecting objects of interest in images was always a compelling task to automate. In recent years this task was more and more explored using deep learning techniques, mostly using region-based convolutional networks. In this project we propose an alternative semantic segmentation technique making use of Generative Adversarial Networks. We consider semantic segmentation to be a domain transfer problem. Thus, we train a feed forward network (FFNN) to receive as input a seed real image and generate as output its segmentation mask.
Comment: Accepted contribution at EEML2021 with poster presentation