SOTAVerified

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 3140 of 179 papers

TitleStatusHype
Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object DetectionCode1
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object DetectionCode1
Few-Shot Object Detection via Association and DIscriminationCode1
Exploring Effective Knowledge Transfer for Few-shot Object DetectionCode1
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object DetectionCode1
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object DetectionCode1
Exploring Robust Features for Few-Shot Object Detection in Satellite ImageryCode1
DETReg: Unsupervised Pretraining with Region Priors for Object DetectionCode1
DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object DetectionCode1
Decoupling Classifier for Boosting Few-shot Object Detection and Instance SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Training-freeAP36.6Unverified
2CD-ViTOAP35.3Unverified
3DE-ViTAP34Unverified
4BIOTAP26.3Unverified
5RISF (SWIN-Large)AP25.5Unverified
6DETReg-ft-full DDETRAP25Unverified
7imTED+ViT-BAP22.5Unverified
8hANMCLAP22.4Unverified
9RISF (Resnet-101)AP21.9Unverified
10DCFSAP19.5Unverified
#ModelMetricClaimedVerifiedStatus
1FS-CDIS (iFS-RCNN+ITL 5-shot)box AP10.36Unverified
2FS-CDIS (MTFA+IMS 5-shot)box AP10.36Unverified
3FS-CDIS (Res101-MTFA+IMS 5-shot)box AP10.36Unverified
4FS-CDIS (Res101-MTFA+ITL 5-shot)box AP9.76Unverified
5FS-CDIS (M-RCNN+ITL 5-shot)box AP9.67Unverified
6FS-CDIS (M-RCNN+IMS 5-shot)box AP9.52Unverified
7FS-CDIS (iFS-RCNN+IMS 5-shot)box AP8.44Unverified
8FS-CDIS (M-RCNN+IMS 3-shot)box AP7.96Unverified
9FS-CDIS (M-RCNN+ITL 3-shot)box AP7.85Unverified
10FS-CDIS (M-RCNN+ITL 2-shot)box AP7.56Unverified
#ModelMetricClaimedVerifiedStatus
1Training-freeAP36.8Unverified
2CD-ViTOAP35.9Unverified
3DE-ViTAP34Unverified
4BIOTAP33.8Unverified
5RISF (SWIN-Large)AP31.9Unverified
6imTED+ViT-BAP30.2Unverified
7DETReg-ft-full DDETRAP30Unverified
8hANMCLAP25Unverified
9RISF (Resnet-101)AP24.4Unverified
10Meta-DETR (Multi-Scale Feature)AP22.9Unverified
#ModelMetricClaimedVerifiedStatus
1best_single_model_valAP47.55Unverified
2htcAP39.05Unverified
3Organizer Provided BaselineAP27.26Unverified
4nullAP25.8Unverified
5Forest R-CNNAP23.2Unverified
6personAP21.82Unverified
7test balloon 6AP16.62Unverified
#ModelMetricClaimedVerifiedStatus
1Training-freeAP26.5Unverified
2hANMCLAP13.4Unverified
3UniFSAP12.7Unverified
4RISFAP11.7Unverified
5DCFSAP10Unverified
6DeFRCNAP9.3Unverified
7DCFSAP8.1Unverified
#ModelMetricClaimedVerifiedStatus
1TestConsistencyAP48.58Unverified
2ps4AP39.67Unverified
3Asynchronous SSLAP37.72Unverified
4CenterNet2AP35.84Unverified
5Organizer Provided BaselineAP26.86Unverified
#ModelMetricClaimedVerifiedStatus
1Grounding DINO 1.5 ProAverage Score66.3Unverified
2MQ-GLIP-TAverage Score57Unverified
3GLIP-TAverage Score50.7Unverified
#ModelMetricClaimedVerifiedStatus
1Grounding DINO 1.5 ProAverage Score54.7Unverified
2MQ-GLIP-TAverage Score43Unverified
3GLIP-TAverage Score38.9Unverified
#ModelMetricClaimedVerifiedStatus
1DETReg (ours)AP30Unverified
#ModelMetricClaimedVerifiedStatus
1UniFSAP18.2Unverified