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Unsupervised Domain Adaptation

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하위 태스크: 1
평가표: 49
보존된 평가 기록: 393

Unsupervised Domain Adaptation is a learning framework to transfer knowledge learned from source domains with a large number of annotated training examples to target domains with unlabeled data only.

Source: Domain-Specific Batch Normalization for Unsupervised Domain Adaptation

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/divyakraman/SAfE-Self-Attention-Based-Unsupervised-Road-Safety-Classification-in-Hazardous-Environments

SS-SFDA : Self-Supervised Source-Free Domain Adaptation for Road Segmentation in Hazardous Environments

https://github.com/divyakraman/SS-SFDA-Self-Supervised-Source-Free-Domain-Adaptation-for-Road-Segmentation-in-Hazardous-Environme

SS-SFDA : Self-Supervised Source-Free Domain Adaptation for Road Segmentation in Hazardous Environments

https://github.com/dmizr/phuber

Deep Residual Learning for Image Recognition

https://github.com/dnddnjs/pytorch-cifar10

Deep Residual Learning for Image Recognition

https://github.com/domainadaptation/salad

Domain-Adversarial Training of Neural Networks

https://github.com/dooleys/fr-nas

Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network

https://github.com/driptaRC/DECISION

Unsupervised Multi-source Domain Adaptation Without Access to Source Data

https://github.com/dssbxx/k_labels_resnet50

Deep Residual Learning for Image Recognition

https://github.com/duchaba/Norwegian_Blue_Parrot_k2fa_AI

Deep Residual Learning for Image Recognition

https://github.com/dv-fenix/Domain-Adaptation

Domain-Adversarial Training of Neural Networks

https://github.com/enzomuschik/distilfnd

Deep Residual Learning for Image Recognition

https://github.com/epic-kitchens/C1-Action-Recognition-TSN-TRN-TSM

Rescaling Egocentric Vision

https://github.com/epic-kitchens/epic-kitchens-slowfast

Rescaling Egocentric Vision

https://github.com/eric-erki/IdenProf

Deep Residual Learning for Image Recognition

https://github.com/erictzeng/adda

Adversarial Discriminative Domain Adaptation

https://github.com/eridgd/WCT-TF

Correlation Alignment for Unsupervised Domain Adaptation

https://github.com/eriklindernoren/Keras-GAN

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

https://github.com/eriklindernoren/PyTorch-GAN

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

https://github.com/erlendd/ddan

Unsupervised Domain Adaptation by Backpropagation

https://github.com/ermolenkodev/da-ssd

Unsupervised Domain Adaptation by Backpropagation

https://github.com/ermongroup/alignflow

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows

https://github.com/estrellaxyu/differential-alignment-for-daod

Align and Distill: Unifying and Improving Domain Adaptive Object Detection

https://github.com/ewinata/CIFAR-10

Deep Residual Learning for Image Recognition

https://github.com/fL0n9/SKFAC-MindSpore

Deep Residual Learning for Image Recognition

https://github.com/fabiofumarola/ultrayolo

Deep Residual Learning for Image Recognition

https://github.com/fabxy/accessibilityCV

Deep Residual Learning for Image Recognition

https://github.com/facebook/fb.resnet.torch

Deep Residual Learning for Image Recognition

https://github.com/facebookarchive/fb.resnet.torch

Deep Residual Learning for Image Recognition

https://github.com/facebookresearch/DomainBed

Domain-Adversarial Training of Neural Networks

https://github.com/facebookresearch/ModelRatatouille

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/facebookresearch/hiera

Deep Residual Learning for Image Recognition

https://github.com/facebookresearch/pycls

Deep Residual Learning for Image Recognition

https://github.com/facebookresearch/stochastic_gradient_push

Deep Residual Learning for Image Recognition

https://github.com/facundoq/transformational_measures_experiments

Deep Residual Learning for Image Recognition

https://github.com/fastai/fastai

Deep Residual Learning for Image Recognition

https://github.com/fchollet/deep-learning-models

Deep Residual Learning for Image Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.