Class-agnostic Object Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

5 shown of 5 papers with code (9 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.

• DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
  21 Jun 2024 1 repository listed Syntology ran 5 of 7 samples · 2 unverified
  We demonstrate the effectiveness of DiPEx through extensive class-agnostic OD and OOD-OD experiments on MS-COCO and LVIS, surpassing other prompting methods by up to 20.
• Detecting Every Object from Events
  8 Apr 2024 1 repository listed
  Object detection is critical in autonomous driving, and it is more practical yet challenging to localize objects of unknown categories: an endeavour known as Class-Agnostic Object Detection (CAOD).
• GOOD: Exploring Geometric Cues for Detecting Objects in an Open World
  22 Dec 2022 1 repository listed
  We address the task of open-world class-agnostic object detection, i.
• MOVE: Unsupervised Movable Object Segmentation and Detection
  14 Oct 2022 1 repository listed Syntology ran 3 of 6 samples · 3 unverified · 6 pointer-only (licence)
  We introduce MOVE, a novel method to segment objects without any form of supervision.
• Class-agnostic Object Detection with Multi-modal Transformer
  22 Nov 2021 1 repository listed
  This has been a long-standing question in computer vision.

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.