# Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras

Source: [Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras](<https://www.sota2.com/research/paper/68fa70261e209131cea49656>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:35:15.802Z

Authors: Divam Gupta

Published: 2023-07-25T02:56:20.000Z

## Abstract

Semantic segmentation plays a vital role in computer vision tasks, enabling precise pixel-level understanding of images. In this paper, we present a comprehensive library for semantic segmentation, which contains implementations of popular segmentation models like SegNet, FCN, UNet, and PSPNet. We also evaluate and compare these models on several datasets, offering researchers and practitioners a powerful toolset for tackling diverse segmentation challenges.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2307.13215>)

[PDF](<https://arxiv.org/pdf/2307.13215.pdf>)