(CVPR 2021) Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166
-
Updated
Mar 5, 2023 - Python
#
domain-shift
Here are 33 public repositories matching this topic...
Domain Generalization via Gradient Surgery
-
Updated
May 3, 2022 - Python
[NeurIPS 2022] The official repository of Expression Learning with Identity Matching for Facial Expression Recognition
pytorch human-computer-interaction optimal-transport facial-expressions facial-expression-recognition valence-arousal feature-normalization domain-shift real-time-demo out-of-distribution-generalization
-
Updated
Nov 29, 2023 - Python
Gpu accelerated vahadane stain normalization for Digital Pathology workflows.
deep-learning pytorch gpu-acceleration digital-pathology pathology domain-adaptation computational-pathology stain-normalization stain-separation domain-shift staintools vahadane
-
Updated
Feb 23, 2024 - Python
NeurIPS 2024 (spotlight): A Textbook Remedy for Domain Shifts Knowledge Priors for Medical Image Analysis
-
Updated
Oct 15, 2024 - Python
Pytorch implementation of Deep Generic Representations for Domain-Generalized Anomalous Sound Detection: https://arxiv.org/abs/2409.05035
unsupervised-learning anomaly-detection domain-adaptation unsupervised-domain-adaptation domain-shift anomalous-sound-detection
-
Updated
Mar 16, 2025 - Python
[NeurIPS 2024] WATT: Weight Average Test-Time Adaptation of CLIP
-
Updated
Sep 26, 2024 - Python
ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions 🚗 🚃
-
Updated
Apr 16, 2024 - Python
LAMDA: Label Matching Deep Domain Adaptation - ICML 2021
optimal-transport domain-adaptation unsupervised-domain-adaptation wasserstein-distance label-shift domain-shift icml-2021
-
Updated
Oct 28, 2021 - Python
Domain-shift Aware Meta-Learning for Domain Generalization in SER
meta-learning speech-emotion-recognition domain-generalization domain-shift speech-emotion-classification mldg
-
Updated
Nov 17, 2022 - Python
Domain Adaptive and Fine-grained Anomaly Detection for Single-cell Sequencing Data and Beyond
-
Updated
Sep 7, 2024 - Python
How to predict uncertainty of regression GNN models under target domain shifts?
regression-models uncertainty-quantification brain-connectivity gnn graph-neural-network domain-shift domain-fracture
-
Updated
Nov 7, 2022 - Python
Code for the paper "Addressing caveats of neural persistence with deep graph persistence".
-
Updated
Nov 29, 2023 - Python
A repository to demonstrate the domain shift between the different domains of the Office-31 dataset. The repository includes feature extraction from the raw images and then analyzing those feature vectors.
-
Updated
Jul 26, 2021 - Python
-
Updated
Aug 25, 2023 - Jupyter Notebook
Visual Drone Detection Dataset for Comprehensive Study of Domain shift
-
Updated
Apr 15, 2025
Repository dedicated to the studies of domain shift in the context of classification of OSCC histopathology images
-
Updated
Jul 15, 2024 - Jupyter Notebook
Final project of Bachelor's degree
-
Updated
Jun 24, 2025 - Jupyter Notebook
Code related to the article "Reducing domain shift in synthetic data augmentation for semantic segmentation of 3D point clouds" submitted to the SMC 2022 conference
-
Updated
Oct 14, 2022 - C++
A lightweight, no-install, GUI-based Python toolbox for detecting, measuring, and visualizing domain shift (data shift) across datasets — all running in your browser on Windows, macOS, or Linux.
python data-science machine-learning gui tabular-data python3 toolbox pca hypothesis-testing umap domain-adaptation streamlit data-drift domain-shift data-shift machine-learning-evaluation machine-learning-robustness domain-shift-detection machine-learning-reliability data-shift-detection
-
Updated
Feb 8, 2026 - Python
Improve this page
Add a description, image, and links to the domain-shift topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the domain-shift topic, visit your repo's landing page and select "manage topics."