Unsupervised Domain Adaptation of Object Detection in Axial CT Images of Lumbar Vertebrae
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Updated
Oct 10, 2024 - Python
Unsupervised Domain Adaptation of Object Detection in Axial CT Images of Lumbar Vertebrae
[AAAI 2024] Prompt-based Distribution Alignment for Unsupervised Domain Adaptation
Pytorch implementation of Deep Generic Representations for Domain-Generalized Anomalous Sound Detection: https://arxiv.org/abs/2409.05035
Official implementation of "Align and Distill: Unifying and Improving Domain Adaptive Object Detection"
[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
[ECCV22] Official Implementation of HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild
Project crafted by Antonio Ferrigno, Giulia Di Fede and Vittorio Di Giorgio for the Advanced Machine Learning course at Politecnico di Torino (2023/2024)
[ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.
[CVPR 2024] "M3-UDA: A New Benchmark for Unsupervised Domain Adaptive Fetal Cardiac Structure Detection" by Bin Pu*, Liwen Wang*, Jiewen Yang*, He Guannan, Xingbo Dong, Li Shengli, Tan Ying, Ming Chen, Zhe Jin, Kenli Li and Xiaomeng Li.
[CVPRW 2021] Rethinking Ensemble-Distillation for Semantic Segmentation Based Unsupervised Domain Adaptation
Project for "Advanced Machine Learning" course at PoliTO. The purpose is to implement a BiSeNet able to perform real-time semantic segmentation task
1st place solution for MICCAI challenge CrossMoDA 2023 (unsupervised domain adaptation for medical images)
1st place solution for MICCAI challenge CrossMoDA 2023
Source code for "Online Unsupervised Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions", ECCV 2022. This is the code has been implemented to perform training and evaluation of UDA approaches in continuous scenarios. The library has been implemented in PyTorch 1.7.1. Some newer versions should work as well.
NeurIPS 2023: Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Pytorch implementation for "Dynamic Instance Domain Adaptation" (DIDA-Net, accepted to IEEE T-IP).
[MICCAI2023] Pytorch implementation for 'Regressing Simulation to Real: Unsupervised Domain Adaptation for Automated Quality Assessment in Transoesophageal Echocardiography'
Semantic Segmentation of Indian Road Scenes through Unsupervised Domain Adaptation
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