Datasets › OPA
OPA (Object Placement Assessment)
Object-Placement-Assessment (OPA) is a task consisting on verifying whether a composite image is plausible in terms of the object placement. The foreground object should be placed at a reasonable location on the background considering location, size, occlusion, semantics, and etc.
OPA is a synthesised dataset for Object Placement Assessment based on COCO dataset. The authors selected unoccluded objects from multiple categories as our candidate foreground objects. The foreground objects are pasted on their compatible background images with random sizes and locations to form composite images, which are sent to human annotators for rationality labeling.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 12 papers for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- OPA
1 variant name, as the archive lists them.
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