Few-shot Instance Segmentation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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

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

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

8 shown of 8 papers with code (13 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.

• Instance-level Few-shot Learning with Class Hierarchy Mining
  15 Apr 2023 1 repository listed Syntology ran 6 of 9 samples · 3 unverified · 7 pointer-only (licence)
  In this paper, we exploit the hierarchical information to leverage discriminative and relevant features of base classes to effectively classify novel objects.
• The Art of Camouflage: Few-Shot Learning for Animal Detection and Segmentation
  15 Apr 2023 1 repository listed
  Camouflaged object detection and segmentation is a new and challenging research topic in computer vision.
• MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
  9 Mar 2023 1 repository listed
  To overcome the disadvantage of the point estimation mechanism, we propose a novel approach, dubbed MaskDiff, which models the underlying conditional distribution of a binary mask, which is conditioned on an object…
• Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentation
  3 Jan 2023 1 repository listed
  Few-Shot Instance Segmentation (FSIS) requires detecting and segmenting novel classes with limited support examples.
• Geodesic-Former: a Geodesic-Guided Few-shot 3D Point Cloud Instance Segmenter
  22 Jul 2022 1 repository listed Syntology ran 1 of 10 samples · 9 unverified
  This paper introduces a new problem in 3D point cloud: few-shot instance segmentation.
• iFS-RCNN: An Incremental Few-shot Instance Segmenter
  31 May 2022 1 repository listed
  This paper addresses incremental few-shot instance segmentation, where a few examples of new object classes arrive when access to training examples of old classes is not available anymore, and the goal is to perform…
• Incremental Few-Shot Instance Segmentation
  11 May 2021 1 repository listed Syntology ran 2 of 8 samples · 6 unverified · 8 pointer-only (licence)
  We learn discriminative embeddings for object instances that are merged into class representatives.
• FAPIS: A Few-shot Anchor-free Part-based Instance Segmenter
  31 Mar 2021 1 repository listed
  This paper is about few-shot instance segmentation, where training and test image sets do not share the same object classes.

Syntology lines on 3 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.