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SOTA
跨域少样本物体检测
Cross Domain Few Shot Object Detection On
Cross Domain Few Shot Object Detection On
评估指标
mAP
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
mAP
Paper Title
Repository
CD-ViTO
60.5
Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector
BIOT(10-Shot)
58.4
Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners
-
BIOT(5-Shot)
53.3
Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners
-
DE-ViT-FT
49.2
Detect Everything with Few Examples
ViTDeT-FT
23.4
Exploring Plain Vision Transformer Backbones for Object Detection
FSCE
15.9
FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding
DeFRCN
15.5
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
TFA w/cos
14.8
Frustratingly Simple Few-Shot Object Detection
Meta-RCNN
14.0
Meta-RCNN: Meta Learning for Few-Shot Object Detection
-
Detic-FT
12.0
Detecting Twenty-thousand Classes using Image-level Supervision
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Cross Domain Few Shot Object Detection On | SOTA | HyperAI超神经