Few-Shot Object Detection
Few-Shot Object Detection is a computer vision task that involves detecting objects in images with limited training data. The goal is to train a model on a few examples of each object class and then use the model to detect objects in new images.
Papers
Showing 1–10 of 179 papers
All datasetsMS-COCO (10-shot)CAMO-FSMS-COCO (30-shot)LVIS v1.0 valMS-COCO (1-shot)LVIS v1.0 test-devODinW-13ODinW-35COCO 2017MS-COCO (5-shot)
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Grounding DINO 1.5 Pro | Average Score | 54.7 | — | Unverified |
| 2 | MQ-GLIP-T | Average Score | 43 | — | Unverified |
| 3 | GLIP-T | Average Score | 38.9 | — | Unverified |