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SotA/Methodology/2D Classification/iRodent

2D Classification on iRodent

Metric: Average mAP (higher is better)

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Results

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#Model↕Average mAP▼AugmentationsPaperDate↕Code
1fine-tuned HRNetw32 pretrained on SuperAnimal (1 fac of data)72.971YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
2fine-tuned HRNetw32 pretrained on AP-10K (1 fac of data)61.635YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
3fine-tuned HRNetw32 pretrained on SuperAnimal (0.01 fac of data)60.853YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
4fine-tuned HRNetw32 pretrained on ImageNet58.857YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
5zero-shot HRNet-w32 pretrained on SuperAnimal-Quadruped58.557YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
6zero-shot AnimalTokenPose pretrained on AP-10K55.415YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
7fine-tuned HRNetw32 pretrained on AP-10K (0.01 fac of data)43.144YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code
8zero-shot HRNet-w32 pretrained on AP-10K40.389YesSuperAnimal pretrained pose estimation models fo...2022-03-14Code