# Fine Hand Segmentation using Convolutional Neural Networks

arXiv: https://arxiv.org/abs/1608.07454 · HTML: https://mlsanity.com/paper/1608.07454/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2016.

## Built on by (most cited first, 1 of 1)

- [BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition](https://mlsanity.com/paper/2408.10518/) (2024)

## Abstract (arXiv)

We propose a method for extracting very accurate masks of hands in egocentric views. Our method is based on a novel Deep Learning architecture: In contrast with current Deep Learning methods, we do not use upscaling layers applied to a low-dimensional representation of the input image. Instead, we extract features with convolutional layers and map them directly to a segmentation mask with a fully connected layer. We show that this approach, when applied in a multi-scale fashion, is both accurate and efficient enough for real-time. We demonstrate it on a new dataset made of images captured in various environments, from the outdoors to offices.