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Few-Shot Object Detection
Few Shot Object Detection On Ms Coco 10 Shot
Few Shot Object Detection On Ms Coco 10 Shot
Metrics
AP
Results
Performance results of various models on this benchmark
Columns
Model Name
AP
Paper Title
Repository
MetaYOLO
5.6
Few-shot Object Detection via Feature Reweighting
MPSR
9.8
Multi-Scale Positive Sample Refinement for Few-Shot Object Detection
imTED+ViT-S
15.0
Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection
DeFRCN
18.5
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
CFA-DeFRCN
19.1
CFA: Constraint-based Finetuning Approach for Generalized Few-Shot Object Detection
-
FSDetView
12.5
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild
SSR-FSD
11.3
Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
-
BIOT
26.3
Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners
-
DAnA-FasterRCNN
18.6
Dual-Awareness Attention for Few-Shot Object Detection
FSOD(Universal-Prototype)
11.0
Universal-Prototype Enhancing for Few-Shot Object Detection
FSDetView + PSP
13.4
Few-Shot Object Detection by Attending to Per-Sample-Prototype
-
DCFS
19.5
Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation
Meta-DETR (Single-Scale Feature)
16.7
Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation
CME
15.1
Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection
RISF (Resnet-101)
21.9
Re-Scoring Using Image-Language Similarity for Few-Shot Object Detection
FSRN (RetinaNet)
15.8
Towards Discriminative and Transferable One-Stage Few-Shot Object Detectors
-
Meta-DETR (Multi-Scale Feature)
17.8
Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation
RISF (SWIN-Large)
25.5
Re-Scoring Using Image-Language Similarity for Few-Shot Object Detection
imTED+ViT-B
22.5
Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection
DE-ViT
34.0
Detect Everything with Few Examples
0 of 32 row(s) selected.
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