Few-Shot Object Detection Leaderboard

MSCOCO-FSOD   PASCAL-VOC-FSOD  

   


The goal of this page is to keep on track with the state-of-the-art (SOTA) for the few-shot object detection.
If your paper is not in the list, please feel free to raise an issue or drop me an e-mail.


PASCAL-VOC FSOD Leaderboard

Edit this leaderboard

Method Venue Year Backbone Detector Paradigm Setting Set1 1/2/3/5/10-shot Set2 1/2/3/5/10-shot Set3 1/2/3/5/10-shot Code
FS-DETR ICCV 2023 R50 DETR without re-training FSOD 45.0 48.5 51.5 52.7 56.1 37.3 41.3 43.4 46.6 49.0 43.8 47.1 50.6 52.1 56.9 -
σ-ADP ICCV 2023 R-101 Faster R-CNN meta-learning FSOD 35.9 40.3 49.8 56.8 65.1 25.6 30.3 41.7 41.8 50.3 33.9 35.6 43.5 47.1 55.9 -
Norm-VAE CVPR 2023 R-101 Faster-RCNN Fine-tuning FSOD 62.1 64.9 67.8 69.2 67.5 39.9 46.8 54.4 54.2 53.6 58.2 60.3 61.0 64.0 65.5 -
MetaAug CVPR 2023 R-101 Faster-RCNN Fine-tuning gFSOD 66.7 69.3 69.8 72.2 72.1 47.7 55.8 61.8 63.9 63.7 64.9 65.8 66.2 69.7 70.2 -
MetaAug CVPR 2023 R-101 Faster-RCNN Fine-tuning FSOD 58.4 62.4 63.2 67.6 67.7 34.0 43.1 51.0 53.6 54.0 55.1 56.6 57.3 62.6 63.7 -
NIFF CVPR 2023 R-101 Faster-RCNN Fine-tuning gFSOD 75.6 76.5 76.7 77.4 76.9 70.0 71.4 73.9 74.4 74.0 74.4 75.8 76.2 76.6 76.7 -
DiGeo CVPR 2023 R-101 Faster-RCNN Fine-tuning gFSOD 69.7 70.6 72.4 75.4 76.1 67.5 68.4 71.4 71.6 73.6 68.6 70.9 72.9 74.4 75.0 PyTorch
ICPE AAAI 2023 R-101 Faster-RCNN Fine-tuning FSOD 54.3 59.5 62.4 65.7 66.2 33.5 40.1 48.7 51.7 52.5 50.9 53.1 55.3 60.6 60.1 PyTorch
VFA AAAI 2023 R-101 Faster-RCNN Fine-tuning FSOD 57.7 64.6 64.7 67.2 67.4 41.4 46.2 51.1 51.8 51.6 48.9 54.8 56.6 59.0 58.9 PyTorch
D&R AAAI 2023 R-101 Faster-RCNN Fine-tuning gFSOD 41.0 51.7 55.7 61.8 65.4 30.7 39.0 42.5 46.6 51.7 37.9 47.1 51.7 56.8 59.5 PyTorch
DCFS NeurIPS 2022 R-101 Faster-RCNN Fine-tuning FSOD 56.6 59.6 62.9 65.6 62.5 29.7 38.7 46.2 48.9 48.1 47.9 51.9 53.3 56.1 59.4 PyTorch
DCFS NeurIPS 2022 R-101 Faster-RCNN Fine-tuning gFSOD 45.8 59.1 62.1 66.8 68.0 31.8 41.7 46.6 50.3 53.7 39.6 52.1 56.3 60.3 63.3 PyTorch
CoCo-RCNN ECCV 2022 R-101 Sparse-RCNN Fine-tuning FSOD 33.5 44.2 50.2 57.5 63.3 25.3 31.0 39.6 43.8 50.1 24.8 36.9 42.8 50.8 57.7 PyTorch
FewX ECCV 2022 R-50 Faster R-CNN Fine-tuning FSOD 40.1 44.2 51.2 62.0 63.0 33.3 33.1 42.3 46.3 52.3 36.1 43.1 43.5 52.0 56.0 PyTorch
MFDC ECCV 2022 R-101 Faster R-CNN Fine-tuning FSOD 63.4 66.3 67.7 69.4 68.1 42.1 46.5 53.4 55.3 53.8 56.1 58.3 59.0 62.2 63.7 PyTorch
TENET ECCV 2022 R-50 - Fine-tuning FSOD 46.7 - 55.4 62.3 66.9 40.3 - 44.7 49.3 52.1 35.5 - 46.0 54.4 54.6 PyTorch
MRSN ECCV 2022 R-101 Faster R-CNN Fine-tuning FSOD 47.6 48.6 57.8 61.9 62.6 31.2 38.3 46.7 47.1 50.6 35.5 30.9 45.6 54.4 57.4 -
KD-DeFRCN ECCV 2022 R-101 Faster R-CNN Fine-tuning FSOD 58.2 62.5 65.1 68.2 67.4 37.6 45.6 52.0 54.6 53.2 53.8 57.7 58.0 62.4 62.2 -
Label, Verify, Correct CVPR 2022 R-101+DINO ViT-S Faster R-CNN Fine-tuning FSOD 54.5 53.2 58.8 63.2 65.7 32.8 29.2 50.7 49.8 50.6 48.4 52.7 55.0 59.6 59.6 PyTorch
FCT CVPR 2022 PVTv2-B2-Li Faster R-CNN meta-learning FSOD 38.5 49.6 53.5 59.8 64.3 25.9 34.2 40.1 44.9 47.4 34.7 43.9 49.3 53.1 56.3 PyTorch
KFSOD CVPR 2022 R-50 Faster-RCN meta-learning FSOD 44.6 - 54.4 60.9 65.8 37.8 - 43.1 48.1 50.4 34.8 - 44.1 52.7 53.9 -
Meta-Faster-RCNN AAAI 2022 R-101 Faster R-CNN meta-learning FSOD 43.0 54.5 60.6 66.1 65.4 27.7 35.5 46.1 47.8 51.4 40.6 46.4 53.4 59.9 58.6 PyTorch
QA-FewDet ICCV 2021 R-101 Faster R-CNN meta-learning FSOD 42.4 51.9 55.7 62.6 63.4 25.9 37.8 46.6 48.9 51.1 35.2 42.9 47.8 54.8 53.5 PyTorch
DeFRCN ICCV 2021 R-101 Faster R-CNN Fine-tuning FSOD 53.6 57.5 61.5 64.1 60.8 30.1 38.1 47.0 53.3 47.9 48.4 50.9 52.3 54.9 57.4 PyTorch
DeFRCN ICCV 2021 R-101 Faster R-CNN Fine-tuning gFSOD 40.2 53.6 58.2 63.6 66.5 29.5 39.7 43.4 48.1 52.8 35.0 38.3 52.9 57.7 60.8 PyTorch
FSOD$^{up}$ ICCV 2021 R-101 Faster R-CNN Fine-tuning gFSOD 43.8 47.8 50.3 55.4 61.7 31.2 30.5 41.2 42.2 48.3 35.5 39.7 43.9 50.6 53.5 PyTorch
FADI NeurIPS 2021 R-101 Faster R-CNN Fine-tuning gFSOD 50.3 54.8 54.2 59.3 63.2 30.6 35.0 40.3 42.8 48.0 45.7 49.7 49.1 55.0 59.6 PyTorch
SRR-FSD CVPR 2021 R-101 Faster R-CNN Fine-tuning FSOD 47.8 50.5 51.3 55.2 56.8 32.5 35.3 39.1 40.8 43.8 40.1 41.5 44.3 46.9 46.4 -
CME CVPR 2021 F-RCNN meta-learning gFSOD 41.5 47.5 50.4 58.2 60.9 27.2 30.2 41.4 42.5 46.8 34.3 39.6 45.1 48.3 51.5 PyTorch
CME CVPR 2021 Meta-YOLO meta-learning gFSOD 17.8 26.1 31.5 44.8 47.5 12.7 17.4 27.1 33.7 40.0 15.7 27.4 30.7 44.9 48.8 PyTorch
DCNet CVPR 2021 R-101 Faster R-CNN meta-learning FSOD 33.9 37.4 43.7 51.1 59.6 23.2 24.8 30.6 36.7 46.6 32.3 34.9 39.7 42.6 50.7
TIP CVPR 2021 R-101 Faster R-CNN meta-learning FSOD 27.7 36.5 43.3 50.2 59.6 22.7 30.1 33.8 40.9 46.9 21.7 30.6 38.1 44.5 50.9
FSCE CVPR 2021 R-101 Faster R-CNN Fine-tuning FSOD 32.9 44.0 46.8 52.9 59.7 23.7 30.6 38.4 43.0 48.5 22.6 33.4 39.5 47.3 54.0 PyTorch
Retentive R-CNN CVPR 2021 R-101 R-CNN Fine-tuning gFSOD 71.3 72.3 72.1 74.0 74.6 66.8 68.4 70.2 70.7 71.5 69.0 70.9 72.3 73.9 74.1 PyTorch
Halluc CVPR 2021 R-101 Faster R-CNN Fine-tuning FSOD 47.0 44.9 46.5 54.7 54.7 26.3 31.8 37.4 37.4 41.2 40.4 42.1 43.3 51.4 49.6 -
TFA ICML 2020 R-101 Faster R-CNN Fine-tuning FSOD 39.8 36.1 44.7 55.7 56.0 23.5 26.9 34.1 35.1 39.1 30.8 34.8 42.8 49.5 49.8 PyTorch
FSDetView ECCV 2020 R-101 Faster R-CNN meta-learning FSOD 24.2 35.3 42.2 49.1 57.4 21.6 24.6 31.9 37.0 45.7 21.2 30.0 37.2 43.8 49.6 PyTorch
MPSR ECCV 2020 R-101 Faster R-CNN Fine-tuning FSOD 41.7 - 51.4 55.2 61.8 24.4 - 39.2 39.9 47.8 35.6 - 42.3 48.0 49.7 PyTorch
NP-RepMet NeurIPS 2020 R-101 Faster R-CNN + DCN Fine-tuning FSOD 37.8 40.3 41.7 47.3 49.4 41.6 43.0 43.4 47.4 49.1 33.3 38.0 39.8 41.5 44.8 MXNet

Contact

e-mail