Few-Shot Object Detection Leaderboard

The goal of this page is to keep on track with the state-of-the-art (SOTA) for the few-shot object detection.
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PASCAL-VOC FSOD Leaderboard

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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
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
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
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
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
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
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
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
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
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
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	-
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
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
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
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	-
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
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	-
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	-
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
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
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	-
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
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
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	-
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	-
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	-
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
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
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
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	-
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
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
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
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
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	-

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Few-Shot Object Detection Leaderboard

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PASCAL-VOC FSOD Leaderboard

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