Few Shot Object Detection On Ms Coco 10 Shot
Metrics
AP
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | AP |
|---|---|
| few-shot-object-detection-via-feature | 5.6 |
| multi-scale-positive-sample-refinement-for | 9.8 |
| integral-migrating-pre-trained-transformer | 15.0 |
| defrcn-decoupled-faster-r-cnn-for-few-shot | 18.5 |
| cfa-constraint-based-finetuning-approach-for | 19.1 |
| few-shot-object-detection-and-viewpoint | 12.5 |
| semantic-relation-reasoning-for-shot-stable | 11.3 |
| balanced-id-ood-tradeoff-transfer-makes-query | 26.3 |
| should-i-look-at-the-head-or-the-tail-dual | 18.6 |
| universal-prototype-augmentation-for-few-shot | 11.0 |
| few-shot-object-detection-by-attending-to-per | 13.4 |
| decoupling-classifier-for-boosting-few-shot | 19.5 |
| meta-detr-few-shot-object-detection-via | 16.7 |
| beyond-max-margin-class-margin-equilibrium | 15.1 |
| re-scoring-using-image-language-similarity | 21.9 |
| towards-discriminative-and-transferable-one | 15.8 |
| meta-detr-few-shot-object-detection-via | 17.8 |
| re-scoring-using-image-language-similarity | 25.5 |
| integral-migrating-pre-trained-transformer | 22.5 |
| detect-every-thing-with-few-examples | 34.0 |
| cross-domain-few-shot-object-detection-via | 35.3 |
| plug-and-play-few-shot-object-detection-with | 13.3 |
| frustratingly-simple-few-shot-object | 10.0 |
| hierarchical-attention-network-for-few-shot | 22.4 |
| fsce-few-shot-object-detection-via | 11.1 |
| lstd-a-low-shot-transfer-detector-for-object | 3.2 |
| few-shot-object-detection-with-attention-rpn | 11.1 |
| plug-and-play-few-shot-object-detection-with | 12.5 |
| meta-learning-to-detect-rare-objects | 7.1 |
| meta-r-cnn-towards-general-solver-for-1 | 8.7 |
| detreg-unsupervised-pretraining-with-region | 25 |
| frustratingly-simple-few-shot-object | 10.0 |