Unsupervised Instance Segmentation

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 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

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

8 shown of 8 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.

• Unsupervised Universal Image Segmentation
  28 Dec 2023 2 repositories listed Syntology ran 13 of 15 samples · 2 unverified
  Several unsupervised image segmentation approaches have been proposed which eliminate the need for dense manually-annotated segmentation masks; current models separately handle either semantic segmentation (e.
• Cut and Learn for Unsupervised Object Detection and Instance Segmentation
  26 Jan 2023 2 repositories listed
  We propose Cut-and-LEaRn (CutLER), a simple approach for training unsupervised object detection and segmentation models.
• Part2Object: Hierarchical Unsupervised 3D Instance Segmentation
  14 Jul 2024 1 repository listed Syntology ran 5 of 10 samples · 5 unverified
  By training Hi-Mask3D on the objects and object parts extracted from Part2Object, we achieve consistent and superior performance compared to state-of-the-art models in various settings, including unsupervised instance…
• DETReg: Unsupervised Pretraining with Region Priors for Object Detection
  8 Jun 2021 1 repository listed Syntology ran 4 of 7 samples · 3 unverified
  Recent self-supervised pretraining methods for object detection largely focus on pretraining the backbone of the object detector, neglecting key parts of detection architecture.
• DARCNN: Domain Adaptive Region-based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images
  3 Apr 2021 1 repository listed
  In the biomedical domain, there is an abundance of dense, complex data where objects of interest may be challenging to detect or constrained by limits of human knowledge.
• DARCNN: Domain Adaptive Region-based Convolutional Neural Network forUnsupervised Instance Segmentation in Biomedical Images
  3 Apr 2021 1 repository listed
  We showcase DARCNN’sperformance for unsupervised instance segmentation on nu-merous biomedical datasets.
• PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images
  11 Sep 2020 1 repository listed
  In this work, we present an unsupervised domain adaptation (UDA) method, named Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation in microscopy images.
• Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting
  5 May 2020 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  More specifically, we first propose a nuclei inpainting mechanism to remove the auxiliary generated objects in the synthesized images.

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.