Open-World Instance Segmentation

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

9 shown of 9 papers with code (14 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.

• Single-Stage Open-world Instance Segmentation with Cross-task Consistency Regularization
  18 Aug 2022 2 repositories listed
  Based on the single-stage instance segmentation framework, we propose a regularization model to predict foreground pixels and use its relation to instance segmentation to construct a cross-task consistency loss.
• v-CLR: View-Consistent Learning for Open-World Instance Segmentation
  2 Apr 2025 1 repository listed
  In this paper, we address the challenging problem of open-world instance segmentation.
• SOS: Segment Object System for Open-World Instance Segmentation With Object Priors
  22 Sep 2024 1 repository listed Syntology ran 0 of 7 samples · 7 unverified · 7 pointer-only (licence)
  We thoroughly study various object priors to generate prompts for SAM, explicitly focusing the foundation model on objects.
• General Object Foundation Model for Images and Videos at Scale
  14 Dec 2023 1 repository listed Syntology ran 8 of 13 samples · 5 unverified
  We present GLEE in this work, an object-level foundation model for locating and identifying objects in images and videos.
• SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning
  12 Aug 2023 1 repository listed Syntology ran 3 of 8 samples · 5 unverified
  In this work, we propose a novel training mechanism termed SegPrompt that uses category information to improve the model's class-agnostic segmentation ability for both known and unknown categories.
• OpenInst: A Simple Query-Based Method for Open-World Instance Segmentation
  28 Mar 2023 1 repository listed
  Fortunately, we have identified two observations that help us achieve the best of both worlds: 1) query-based methods demonstrate superiority over dense proposal-based methods in open-world instance segmentation, and 2)…
• Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
  8 Mar 2023 1 repository listed
  Our approach outperforms the previous state of the art by significant margins on both open-vocabulary panoptic and semantic segmentation tasks.
• ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR Data
  8 Mar 2023 1 repository listed
  In this paper, we present a flexible and effective OIS framework for LiDAR point cloud that can accurately segment both known and unknown instances (i.
• Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity
  12 Apr 2022 1 repository listed Syntology ran 11 of 20 samples · 9 unverified · 20 pointer-only (licence)
  From PA we construct a large set of pseudo-ground-truth instance masks; combined with human-annotated instance masks we train GGNs and significantly outperform the SOTA on open-world instance segmentation on various…

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.