fungtion / Dann_py3
Licence: mit
python 3 pytorch implementation of DANN
Stars: ✭ 164
Programming Languages
Projects that are alternatives of or similar to Dann py3
Awesome Transfer Learning
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
Stars: ✭ 1,349 (+722.56%)
Mutual labels: domain-adaptation
Mfr
Learning Meta Face Recognition in Unseen Domains, CVPR, Oral, 2020
Stars: ✭ 127 (-22.56%)
Mutual labels: domain-adaptation
Cdcl Human Part Segmentation
Repository for Paper: Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation (TCSVT20)
Stars: ✭ 143 (-12.8%)
Mutual labels: domain-adaptation
Lsd Seg
Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
Stars: ✭ 99 (-39.63%)
Mutual labels: domain-adaptation
Monoculardepth Inference
Inference pipeline for the CVPR paper entitled "Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer" (http://www.atapour.co.uk/papers/CVPR2018.pdf).
Stars: ✭ 115 (-29.88%)
Mutual labels: domain-adaptation
Neuraldialog Zsdg
PyTorch codebase for zero-shot dialog generation SIGDIAL 2018, It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU
Stars: ✭ 131 (-20.12%)
Mutual labels: domain-adaptation
Ddc Transfer Learning
A simple implementation of Deep Domain Confusion: Maximizing for Domain Invariance
Stars: ✭ 83 (-49.39%)
Mutual labels: domain-adaptation
Squeezesegv2
Implementation of SqueezeSegV2, Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
Stars: ✭ 154 (-6.1%)
Mutual labels: domain-adaptation
Generate to adapt
Implementation of "Generate To Adapt: Aligning Domains using Generative Adversarial Networks"
Stars: ✭ 120 (-26.83%)
Mutual labels: domain-adaptation
Domain Adaptive Faster Rcnn Pytorch
Domain Adaptive Faster R-CNN in PyTorch
Stars: ✭ 135 (-17.68%)
Mutual labels: domain-adaptation
Convolutional Handwriting Gan
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation (CVPR20)
Stars: ✭ 107 (-34.76%)
Mutual labels: domain-adaptation
Opencompounddomainadaptation Ocda
Pytorch implementation for "Open Compound Domain Adaptation" (CVPR 2020 ORAL)
Stars: ✭ 114 (-30.49%)
Mutual labels: domain-adaptation
Shot
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
Stars: ✭ 134 (-18.29%)
Mutual labels: domain-adaptation
Detectron Self Train
A PyTorch Detectron codebase for domain adaptation of object detectors.
Stars: ✭ 99 (-39.63%)
Mutual labels: domain-adaptation
Dta.pytorch
Official implementation of Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation, to be presented at ICCV 2019.
Stars: ✭ 144 (-12.2%)
Mutual labels: domain-adaptation
Seanet
Self-Ensembling Attention Networks: Addressing Domain Shift for Semantic Segmentation
Stars: ✭ 90 (-45.12%)
Mutual labels: domain-adaptation
Dise Domain Invariant Structure Extraction
Pytorch Implementation -- All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation, CVPR 2019
Stars: ✭ 129 (-21.34%)
Mutual labels: domain-adaptation
Transferlearning Tutorial
《迁移学习简明手册》LaTex源码
Stars: ✭ 2,122 (+1193.9%)
Mutual labels: domain-adaptation
Cbst
Code for <Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training> in ECCV18
Stars: ✭ 146 (-10.98%)
Mutual labels: domain-adaptation
This is a pytorch implementation of the paper Unsupervised Domain Adaptation by Backpropagation
Environment
- Pytorch 1.6
- Python 3.8.5
Network Structure
Dataset
First, download target dataset mnist_m from pan.baidu.com fetch code: kjan or Google Drive, and put mnist_m dataset into dataset/mnist_m, the structure is as follows:
--dataset--mnist_m--mnist_m_train
|--mnist_m_test
|--mnist_m_train_labels.txt
|--mnist_m_test_labels.txt
|--.gitkeep
Training
Then, run python main.py
Docker
- build image
docker build -t pytorch_dann .
- run docker container
docker run -it --runtime=nvidia \
-u $(id -u):$(id -g) \
-v /YOUR/DANN/PROJECT/dataset:/DANN/dataset \
-v /YOUR/DANN/PROJECT/models:/DANN/models \
pytorch_dann:latest \
python main.py
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].