Semi-Supervised Instance Segmentation

Benchmarks archive 2025-07-28

6 leaderboard tables shown for this task, 6 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (19 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.

• CenterMask : Real-Time Anchor-Free Instance Segmentation
  15 Nov 2019 8 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  We hope that CenterMask and VoVNetV2 can serve as a solid baseline of real-time instance segmentation and backbone network for various vision tasks, respectively.
• BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
  12 May 2018 4 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving.
• Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance Segmentation
  7 Feb 2024 1 repository listed
  The model has two key designs: a low-resolution denoising (LRD) module and a cross-RoI contrastive learning (CRC) module.
• Pseudo-label Alignment for Semi-supervised Instance Segmentation
  10 Aug 2023 1 repository listed
  Through extensive experiments conducted on the COCO and Cityscapes datasets, we demonstrate that PAIS is a promising framework for semi-supervised instance segmentation, particularly in cases where labeled data is…
• Guided Distillation for Semi-Supervised Instance Segmentation
  3 Aug 2023 1 repository listed
  Although instance segmentation methods have improved considerably, the dominant paradigm is to rely on fully-annotated training images, which are tedious to obtain.
• Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
  5 Jun 2023 1 repository listed
  Experiments on three datasets demonstrate the good generality of our method, which outperforms other image-level weakly supervised methods for nuclei instance segmentation, and achieves comparable performance to…
• The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation
  27 Mar 2023 1 repository listed Syntology ran 1 of 11 samples · 10 unverified
  In this paper, we introduce a novel learning scheme named weakly semi-supervised instance segmentation (WSSIS) with point labels for budget-efficient and high-performance instance segmentation.
• Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?
  25 Mar 2022 1 repository listed
  We construct a framework for semi-supervised instance segmentation by assigning pixel-level pseudo labels.
• Test-time Adaptation with Slot-Centric Models
  21 Mar 2022 1 repository listed Syntology ran 11 of 14 samples · 3 unverified · 14 pointer-only (licence)
  In our work, we find evidence that these losses are insufficient for the task of scene decomposition, without also considering architectural inductive biases.
• ContrastMask: Contrastive Learning to Segment Every Thing
  18 Mar 2022 1 repository listed
  In this framework, annotated masks of seen categories and pseudo masks of unseen categories serve as a prior for contrastive learning, where features from the mask regions (foreground) are pulled together, and are…
• Learning Saliency Propagation for Semi-Supervised Instance Segmentation
  1 Jun 2020 1 repository listed
  Due to the high annotation cost, modeling becomes more difficult because of the limited amount of supervision.

Syntology lines on 4 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.