Pseudo Label Filtering

Benchmarks archive 2025-07-28

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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

11 shown of 11 papers with code (26 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.

• EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenes
  12 Oct 2023 2 repositories listed
  Self-supervised monocular depth estimation holds significant importance in the fields of autonomous driving and robotics.
• Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation
  21 Feb 2025 1 repository listed
  Extensive experiments on the Pascal VOC 2012 and Cityscapes demonstrate that our method achieves state-of-the-art performance.
• PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation
  8 Sep 2024 1 repository listed Syntology ran 13 of 19 samples · 6 unverified · 19 pointer-only (licence)
  In this paper, we propose a simple yet effective semi-supervised learning framework, termed Progressive Mean Teachers (PMT), for medical image segmentation, whose goal is to generate high-fidelity pseudo labels by…
• Less is More: Pseudo-Label Filtering for Continual Test-Time Adaptation
  3 Jun 2024 1 repository listed
  Continual Test-Time Adaptation (CTTA) aims to adapt a pre-trained model to a sequence of target domains during the test phase without accessing the source data.
• Uncertainty-Aware Pseudo-Label Filtering for Source-Free Unsupervised Domain Adaptation
  17 Mar 2024 1 repository listed
  Source-free unsupervised domain adaptation (SFUDA) aims to enable the utilization of a pre-trained source model in an unlabeled target domain without access to source data.
• FishSegSSL: A Semi-Supervised Semantic Segmentation Framework for Fish-Eye Images
  15 Mar 2024 1 repository listed
  In this study, we explore and benchmark two popular semi-supervised methods from the perspective image domain for fish-eye image segmentation.
• Semi-Supervised Semantic Segmentation With Region Relevance
  23 Apr 2023 1 repository listed
  The most common approach is to generate pseudo-labels for unlabeled images to augment the training data.
• Probabilistic Domain Adaptation for Biomedical Image Segmentation
  21 Mar 2023 1 repository listed
  We further study joint and separate source-target training strategies and evaluate our method on three challenging domain adaptation tasks for biomedical segmentation.
• Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation
  19 Oct 2022 1 repository listed
  Current SSL approaches use an initially supervised trained model to generate predictions for unlabelled images, called pseudo-labels, which are subsequently used for training a new model from scratch.
• Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory
  16 Aug 2022 1 repository listed
  This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery.
• Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering
  6 Jun 2022 1 repository listed Syntology ran 6 of 6 samples · 0 unverified
  Test-time training (TTT) emerges as a solution to this adaptation under a realistic scenario where access to full source domain data is not available and instant inference on target domain is required.

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.