Object Detection on DeepFish

Metric: mAP (higher is better)

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#	Model↕	mAP▼	Extra Data	Paper	Date↕	Code
1	ETS	44.1	Yes	Enhance Then Search: An Augmentation-Search Stra...	2025-04-06	Code
2	CDFormer(w/FT)	35.5	No	CDFormer: Cross-Domain Few-Shot Object Detection...	2025-05-02	Code
3	Training-free(w/o FT)	29.6	No	No time to train! Training-Free Reference-Based ...	2025-07-03	Code
4	CDFormer(w/o FT)	25.7	No	CDFormer: Cross-Domain Few-Shot Object Detection...	2025-05-02	Code
5	CD-ViTO	22.3	No	Cross-Domain Few-Shot Object Detection via Enhan...	2024-02-05	Code
6	DE-ViT-FT	21.3	No	Detect Everything with Few Examples	2023-09-22	Code
7	Detic-FT	17.9	No	Detecting Twenty-thousand Classes using Image-le...	2022-01-07	Code
8	ViTDeT-FT	6.5	No	Exploring Plain Vision Transformer Backbones for...	2022-03-30	Code
9	DE-ViT(w/o FT)	2.1	No	Detect Everything with Few Examples	2023-09-22	Code
10	Detic(w/o FT)	0.9	No	Detecting Twenty-thousand Classes using Image-le...	2022-01-07	Code

#1ETSSOTA
44.1
mAP· Extra Data· 2025-04-06
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection Code
#2CDFormer(w/FT)
35.5
mAP· 2025-05-02
CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion Code
#3Training-free(w/o FT)
29.6
mAP· 2025-07-03
No time to train! Training-Free Reference-Based Instance Segmentation Code
#4CDFormer(w/o FT)
25.7
mAP· 2025-05-02
CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion Code
#5CD-ViTOSOTA
22.3
mAP· 2024-02-05
Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector Code
#6DE-ViT-FTSOTA
21.3
mAP· 2023-09-22
Detect Everything with Few Examples Code
#7Detic-FTSOTA
17.9
mAP· 2022-01-07
Detecting Twenty-thousand Classes using Image-level Supervision Code
#8ViTDeT-FT
6.5
mAP· 2022-03-30
Exploring Plain Vision Transformer Backbones for Object Detection Code
#9DE-ViT(w/o FT)
2.1
mAP· 2023-09-22
Detect Everything with Few Examples Code
#10Detic(w/o FT)
0.9
mAP· 2022-01-07
Detecting Twenty-thousand Classes using Image-level Supervision Code