Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation

04/30/2021
by   Arnesh Kumar Issar, et al.
11

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.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 2

page 3

page 8

page 10

04/24/2019

Bidirectional Learning for Domain Adaptation of Semantic Segmentation

Domain adaptation for semantic image segmentation is very necessary sinc...
05/17/2021

PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training

Unsupervised domain adaptation is a promising technique for semantic seg...
02/09/2018

Natural Language Inference over Interaction Space: ICLR 2018 Reproducibility Report

We have tried to reproduce the results of the paper "Natural Language In...
10/12/2019

Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation

Recent works on domain adaptation exploit adversarial training to obtain...
01/26/2020

Reproducibility Challenge NeurIPS 2019 Report on "Competitive Gradient Descent"

This is a report for reproducibility challenge of NeurlIPS 2019 on the p...
06/22/2020

ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks

Computational notebooks have gained widespread adoption among researcher...
11/30/2019

[Re] Learning to Learn By Self-Critique

This work is a reproducibility study of the paper of Antoniou and Storke...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.