Abstract: Few-shot semantic segmentation (FSS) is of tremendous potential for data-scarce scenarios, particularly in medical segmentation tasks with merely a few labeled data. Most of the existing FSS ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Abstract: Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to ...

The goal of the project is to inference a deep learning semantic segmentation model on a webcam video stream in Linux in order to remove background and provide a clean video stream with a person only.

This project demonstrates instance segmentation using Mask R-CNN with the OpenCV DNN module. The model is pre-trained on the COCO dataset and can detect and segment multiple object classes in images.