Unsupervised Domain Adaptation for Semantic Segmentation
-
Updated
Mar 10, 2020
Unsupervised Domain Adaptation for Semantic Segmentation
This is the official implementation of "Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation".
PyTorch implementation of "Generate To Adapt: Aligning Domains using Generative Adversarial Networks"
Aims to help emergency responders during crises (ASONAM '20)
Implementation of Cyclist Pressure Research Paper
Unofficial PyTorch implementation of Domain-Adversarial Training of Neural Networks
Repository containing the Unsupervised Domain Adaptation project developed for the Deep Learning course of the Master's degree in Computer Science at University of Trento
Implementation of DeepJDOT in Keras
Deep Learning project for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation PyTorch
A class-based styling approach for Real-time Domain Adaptation in Semantic Segmentation
Implementation of "Strong-Weak Distribution Alignment for Adaptive Object Detection"(CVPR 2019)
Semantic-adaptive Message Broadcasting for Transformer-based UDA
Semantic Segmentation of Indian Road Scenes through Unsupervised Domain Adaptation
Official Implementation of NVC: Robust Unsupervised Domain Adaptation through Negative-View Regularization
[IEEE TMI 2022] Official Implementation for "LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation"
Unofficial PyTorch implementation of Maximum Domain Confusion loss for Unsupervised Domain Adaptation
[MICCAI 2022] Official Implementation for "Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation"
Add a description, image, and links to the unsupervised-domain-adaptation topic page so that developers can more easily learn about it.
To associate your repository with the unsupervised-domain-adaptation topic, visit your repo's landing page and select "manage topics."