Semi-Supervised Domain Generalization

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Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (17 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Towards Generalizing to Unseen Domains with Few Labels
  18 Mar 2024 2 repositories listed
  Existing domain generalization (DG) methods which are unable to exploit unlabeled data perform poorly compared to semi-supervised learning (SSL) methods under SSDG setting.
• MixStyle Neural Networks for Domain Generalization and Adaptation
  5 Jul 2021 2 repositories listed
  MixStyle is easy to implement with a few lines of code, does not require modification to training objectives, and can fit a variety of learning paradigms including supervised domain generalization, semi-supervised…
• Semi-Supervised Domain Generalization with Stochastic StyleMatch
  1 Jun 2021 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  We find that the DG methods, which by design are unable to handle unlabeled data, perform poorly with limited labels in SSDG; the SSL methods, especially FixMatch, obtain much better results but are still far away from…
• Unlocking the Potential of Unlabeled Data in Semi-Supervised Domain Generalization
  18 Mar 2025 1 repository listed
  To the best of our knowledge, we are the first to explore a method for incorporating the unconfident-unlabeled samples that were previously disregarded in SSDG setting.
• Domain-Guided Weight Modulation for Semi-Supervised Domain Generalization
  4 Sep 2024 1 repository listed
  In search of this endeavor, we study the challenging problem of semi-supervised domain generalization (SSDG), where the goal is to learn a domain-generalizable model while using only a small fraction of labeled data and…
• The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation
  16 Jul 2024 1 repository listed
  Despite the recent success of domain generalization in medical image segmentation, voxel-wise annotation for all source domains remains a huge burden.
• Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization
  25 Jan 2024 1 repository listed
  A key challenge, faced by the best-performing SSL-based SSDG methods, is selecting accurate pseudo-labels under multiple domain shifts and reducing overfitting to source domains under limited labels.
• Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
  17 Oct 2023 1 repository listed Syntology ran 7 of 19 samples · 12 unverified · 19 pointer-only (licence)
  As a result, there is growing interest in using semi-supervised learning (SSL) techniques to train models with limited labeled data.
• Semi-Supervised Domain Generalization for Object Detection via Language-Guided Feature Alignment
  24 Sep 2023 1 repository listed
  Existing domain adaptation (DA) and generalization (DG) methods in object detection enforce feature alignment in the visual space but face challenges like object appearance variability and scene complexity, which make…
• Semi-Supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo Labels
  30 Sep 2022 1 repository listed
  Our main goal is to improve the quality of pseudo labels under extreme MRI Analysis with various domains.
• Semi-Supervised Domain Generalization with Evolving Intermediate Domain
  19 Nov 2021 1 repository listed
  From this perspective, we introduce a novel paradigm of DG, termed as Semi-Supervised Domain Generalization (SSDG), to explore how the labeled and unlabeled source domains can interact, and establish two settings,…

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.