Papers with Code 아카이브
Unsupervised Domain Adaptation
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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/Backdrop9019/pytorch_adda_mixup
https://github.com/Baichenjia/Resnet
https://github.com/BalrajAshwath/Adversarial-Domain_Adaptation_Paper_Implementations
https://github.com/Bao-Jiarong/ResNet
https://github.com/Burf/ModelSoups
https://github.com/Burf/ResNet-Tensorflow2
https://github.com/CVxTz/face_age_gender
https://github.com/CanshangD/ResNet_tensorflow2.0
https://github.com/Carl0520/ADDA-pytorch
https://github.com/Carl0520/DANN_pytorch-
https://github.com/CellSMB/EM-net
https://github.com/ChanghwaPark/CCADA
Joint Contrastive Learning for Unsupervised Domain Adaptation
https://github.com/ChangweiZhang/Awesome-WindowsML-ONNX-Models
https://github.com/Chao-Chen-Hao/Rethinking-EnD-SegUDA
Rethinking Ensemble-Distillation for Semantic Segmentation Based Unsupervised Domain Adaptation
https://github.com/ChrisAllenMing/Mixup_for_UDA
https://github.com/ChristmasStory/TransReID-main
Person Transfer GAN to Bridge Domain Gap for Person Re-Identification
https://github.com/Claydon-Wang/OFTTA
https://github.com/CocoSungMin/Gachon_SW_Colorization_Contest
https://github.com/CodeChefVIT/VOID
https://github.com/CorneliusHsiao/FoodMethodGAN
https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork
https://github.com/CryptoSalamander/pytorch_paper_implementation
https://github.com/CtrlZ1/Domain-Adaptation-Algorithms
Learning Transferable Features with Deep Adaptation Networks
https://github.com/CtrlZ1/Domain-Adaptation-Algorithms/tree/main/pytorch-DeepJDOT
DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation
https://github.com/CtrlZ1/Domain-Adaptive-CodeBase
Learning Transferable Features with Deep Adaptation Networks
https://github.com/D-X-Y/ResNeXt-DenseNet
https://github.com/DableUTeeF/keras-efficientnet
https://github.com/DaikiTanak/manifold_mixup
https://github.com/Darth-Kronos/Unsupervised-Domain-Adaptation
https://github.com/Deci-AI/super-gradients
https://github.com/DeepMark/deepmark
https://github.com/DelTA-Lab-IITK/CADA
https://github.com/Demonhesusheng/Reid
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/DengpanFu/LUPerson
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
https://github.com/Diegomangasco/Vision-Language-AML
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.