# Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation

Source: [Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation](<https://www.sota2.com/research/paper/68fa69d11e209131cea245a3>)

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

Data updated: 2025-10-25T23:09:38.543Z

Authors: Arnesh Kumar Issar, Kirtan Mali, Aryan Mehta, Karan Uppal, Saurabh Mishra, Debashish Chakravarty

Published: 2021-04-30T04:20:35.000Z

## Abstract

The following paper is a reproducibility report for "FDA: Fourier Domain Adaptation for Semantic Segmentation" published in the CVPR 2020 as part of the ML Reproducibility Challenge 2020. The original code was made available by the author. The well-commented version of the code containing all ablation studies performed derived from the original code along with WANDB integration is available at \<github.com/thefatbandit/FDA\> with proper instructions to execute experiments in README.

## 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/2104.14749>)

[PDF](<https://arxiv.org/pdf/2104.14749.pdf>)