https://github.com/Haoxiang-Wang/gradual-domain-adaptation
공식 코드Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond
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/HeliosZhao/M3L
공식 코드https://github.com/HopkinsKwong/MFM-DA
공식 코드https://github.com/IdanAchituve/DefRec_and_PCM
공식 코드Curvature Diversity-Driven Deformation and Domain Alignment for Point Cloud
https://github.com/IssamLaradji/M-ADDA
공식 코드M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning
https://github.com/Ivsucram/ACDC
공식 코드https://github.com/JTRNEO/SynRS3D
공식 코드https://github.com/Jiaolong/ss-da-consistency
공식 코드https://github.com/JingWang18/Discriminative-Feature-Alignment
공식 코드https://github.com/JoseLGomez/Co-training_SemSeg_UDA
공식 코드Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
https://github.com/Jun-Pu/UCOS-DA
공식 코드Unsupervised Camouflaged Object Segmentation as Domain Adaptation
https://github.com/Junjue-Wang/LoveDA
공식 코드LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
https://github.com/Junjue-Wang/LoveNAS
공식 코드LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
https://github.com/KaimingHe/resnet-1k-layers
공식 코드https://github.com/KaiyangZhou/Dassl.pytorch
공식 코드https://github.com/KaiyangZhou/deep-person-reid
공식 코드Learning Generalisable Omni-Scale Representations for Person Re-Identification
https://github.com/KaiyangZhou/mixstyle-release
공식 코드MixStyle Neural Networks for Domain Generalization and Adaptation
https://github.com/KeleiHe/BiGL
공식 코드https://github.com/KeleiHe/DAAN
공식 코드Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition
https://github.com/KevinMusgrave/powerful-benchmarker
공식 코드Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation
https://github.com/KhaLee2307/StrDA
공식 코드Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text Recognition
https://github.com/LIVIAETS/MT-MTDA
공식 코드Unsupervised Multi-Target Domain Adaptation Through Knowledge Distillation
https://github.com/LL-a-VO/VLLaVO
공식 코드https://github.com/LTTM/LSR
공식 코드Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
https://github.com/LTTM/UDAclustering
공식 코드Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings
https://github.com/LcDog/DomainAdaptiveReID
공식 코드Unsupervised Domain Adaptive Re-Identification: Theory and Practice
https://github.com/LeiTian-qj/CMMS
공식 코드Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning
https://github.com/Li-aobo/DGQA
공식 코드https://github.com/LittleWat/multichannel-semseg-with-uda
공식 코드Multichannel Semantic Segmentation with Unsupervised Domain Adaptation
https://github.com/Liuhong99/CST
공식 코드https://github.com/MIPT-Oulu/RobustCartilageSegmentation
공식 코드https://github.com/McGill-NLP/MLQuestions
공식 코드https://github.com/Minminhfut/SSRLDACode
공식 코드Semi-supervised representation learning via dual autoencoders for domain adaptation
https://github.com/MultifacetedNLP/Web-Agents-Unsupervised
공식 코드Grounded Language Agent for Product Search via Intelligent Web Interactions
https://github.com/NVlabs/DG-Net-PP
공식 코드Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification
https://github.com/Natlem/M-HTCN
공식 코드Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.