Partially Labeled Datasets

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (29 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.

• Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging
  10 Jul 2024 2 repositories listed
  First, CNNs predict on unlabeled data per label type and then the transformer learns from these predictions with label-specific heads.
• Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image Segmentation
  5 Sep 2024 1 repository listed
  However, the limited availability of labeled foreground organs and the absence of supervision to distinguish unlabeled foreground organs from the background pose a significant challenge, which leads to a distribution…
• AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning
  21 Jul 2024 1 repository listed
  Specifically, the disambiguation network is trained with self-training PLL task to learn label confidence, while the auxiliary network is trained in a supervised learning paradigm to learn from the noisy pairwise…
• Predicting fluorescent labels in label-free microscopy images with pix2pix and adaptive loss in Light My Cells challenge
  22 Jun 2024 1 repository listed
  Recently, in silico labeling has emerged as a promising alternative, aiming to use machine learning models to directly predict the fluorescently labeled images from label-free microscopy.
• Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery
  23 Aug 2023 1 repository listed Syntology ran 3 of 6 samples · 3 unverified · 6 pointer-only (licence)
  Generalized Continual Category Discovery (GCCD) tackles learning from sequentially arriving, partially labeled datasets while uncovering new categories.
• Learning from partially labeled data for multi-organ and tumor segmentation
  13 Nov 2022 1 repository listed
  To address this, we propose a Transformer based dynamic on-demand network (TransDoDNet) that learns to segment organs and tumors on multiple partially labeled datasets.
• Federated Multi-organ Segmentation with Inconsistent Labels
  14 Jun 2022 1 repository listed
  Extensive experiments on six public abdominal CT datasets show that our Fed-MENU method can effectively obtain a federated learning model using the partially labeled datasets with superior performance to other models…
• DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets
  20 Nov 2020 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  To address this, we propose a dynamic on-demand network (DoDNet) that learns to segment multiple organs and tumors on partially labeled datasets.
• Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT
  5 Sep 2020 1 repository listed
  For example, DeepLesion is such a large-scale CT image dataset with lesions of various types, but it also has many unlabeled lesions (missing annotations).
• Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction
  1 Jan 2020 1 repository listed
  Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation.

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.