Alternatives and similar repositories for DSBF

Users that are interested in DSBF are comparing it to the libraries listed below

• BIT-DA / SCDA
  [ICCV 2021] Code release for "Semantic Concentration for Domain adaptation"
  ☆22Updated 4 years ago
• Learning-group123 / CAiDA
  Code for CAiDA
  ☆24Updated 3 years ago
• VisionLearningGroup / CDS
  CDS: Cross-Domain Self-supervised Pre-training
  ☆27Updated 3 years ago
• lileicv / PDEN
  ☆39Updated 4 years ago
• acmi-lab / Open-Set-Label-Shift
  Code and results accompanying our paper titled Domain Adaptation under Open Set Label Shift
  ☆31Updated 2 years ago
• hathawayxxh / CRCKD
  The source code of 'Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification' (MICCAI 2021)
  ☆18Updated 3 years ago
• lilyht / CIL-MGRB
  PyTorch implementation of MGRB (TKDE2022)
  ☆10Updated 2 years ago
• VisionLearningGroup / Benchmark_Domain_Transfer
  ☆18Updated 3 years ago
• Albert0147 / NRC_SFDA
  Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'
  ☆77Updated 2 years ago
• mousecpn / L2A-OT
  This repository is an unofficial implementation in PyTorch for Learning to Generate Novel Domains for Domain Generalization
  ☆23Updated 3 years ago
• lblaoke / TLC
  PyTorch implementation of the paper "Trustworthy Long-Tailed Classification" (CVPR 2022)
  ☆61Updated last year
• ChrisAllenMing / LtC-MSDA
  Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).
  ☆73Updated 3 years ago
• deep-real / UMGUD
  The Pytorch implementation for "Uncertainty-guided Model Generalization to Unseen Domains" (CVPR 2021)
  ☆22Updated 3 years ago
• hamanhbui / mDSDI
  Exploiting Domain-Specific Features to Enhance Domain Generalization (NeurIPS 2021).
  ☆28Updated 3 years ago
• Liuhong99 / CST
  Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021)
  ☆53Updated 3 years ago
• zhengzangw / PCS-FUDA
  Official implementation of PCS in essay "Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation"
  ☆107Updated 4 years ago
• Gorilla-Lab-SCUT / UB2DA
  This repository provides code for the paper ---- On Universal Black-Box Domain Adaptation.
  ☆10Updated 3 years ago
• Albert0147 / G-SFDA
  code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'
  ☆107Updated 3 years ago
• tim-learn / ATDOC
  code released for our CVPR 2021 paper "Domain Adaptation with Auxiliary Target Domain-Oriented Classifier"
  ☆58Updated 2 years ago
• tim-learn / DINE
  code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"
  ☆81Updated last year
• lucasmansilla / DGvGS
  Domain Generalization via Gradient Surgery
  ☆50Updated 3 years ago
• LeoXinhaoLee / Imbalanced-Source-free-Domain-Adaptation
  Code released for our ACM MM 2021 paper "Imbalanced Source-free Domain Adaptation".
  ☆21Updated 3 years ago
• VisionLearningGroup / OP_Match
  ☆59Updated 2 years ago
• LeeHyuck / ABC
  pytorch implementation of ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
  ☆38Updated 9 months ago
• Albert0147 / AaD_SFDA
  Code for our NeurIPS 2022 (spotlight) paper 'Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation'
  ☆73Updated 8 months ago
• LeoXinhaoLee / AMS
  Code released for our ECCV 2022 paper "Interpretable Open-Set Domain Adaptation via Angular Margin Separation".
  ☆21Updated 2 years ago
• roysubhankar / uncertainty-sfda
  PyTorch code for Uncertainty-guided Source-free Domain Adaptation
  ☆36Updated 3 years ago
• Vanint / CoUDA
  This project provides the source code for “Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis (IEEE TIP 2020)”.
  ☆11Updated 4 years ago
• iCVTEAM / Dara
  Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning TPAMI 2023
  ☆22Updated last year
• YU1ut / Multi-Task-Curriculum-Framework-for-Open-Set-SSL
  Code for "Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning"
  ☆24Updated 5 years ago