Cross Domain Few Shot Object Detection On 4
Metriken
mAP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | mAP |
|---|---|
| fsce-few-shot-object-detection-via | 12.0 |
| defrcn-decoupled-faster-r-cnn-for-few-shot | 12.1 |
| detecting-twenty-thousand-classes-using-image | 16.8 |
| frustratingly-simple-few-shot-object | 11.8 |
| meta-rcnn-meta-learning-for-few-shot-object | 11.2 |
| balanced-id-ood-tradeoff-transfer-makes-query | 18.0 |
| cross-domain-few-shot-object-detection-via | 7.0 |
| exploring-plain-vision-transformer-backbones | 15.8 |
| detect-every-thing-with-few-examples | 5.4 |
| balanced-id-ood-tradeoff-transfer-makes-query | 20.4 |