Computer Vision: Deep Dive into Object Segmentation Approaches

Computer Vision: Deep Dive into Object Segmentation Approaches

연구 분야: Artificial Intelligence

학회: KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Image segmentation is the task of associating pixels in an image with their respective object class labels. It has a wide range of applications in many industries including healthcare, transportation, robotics, fashion, home improvement, and tourism. Many deep learning-based approaches have been developed for image-level object recognition and pixel-level scene understanding - with the latter requiring a much denser annotation of scenes with a large set of objects. This tutorial provides an end-to-end pipeline for performing image segmentation using the state-of-art deep learning approaches and public datasets. The hands-on session will provide instructions for dataset customization, transformation, and training, validating, and testing segmentation models. The goal of this tutorial is to provide participants with a strong understanding of building image segmentation models for downstream applications.