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Animal Pose Estimation On Horse 10
Metrics
Normalized Error (OOD)
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| SuperAnimal-Quadruped HRNet-w32 | 0.1091 | SuperAnimal pretrained pose estimation models for behavioral analysis | |
| DeepLabCut-EfficientNet-B6 | - | Pretraining boosts out-of-domain robustness for pose estimation | |
| DeepLabCut-MOBILENETV2-1 | - | Pretraining boosts out-of-domain robustness for pose estimation | |
| DeepLabCut-EfficientNet-B4 | - | Pretraining boosts out-of-domain robustness for pose estimation | |
| mmpose HRNet-w32 (w/ImageNet pretrained weights) | 0.179 | SuperAnimal pretrained pose estimation models for behavioral analysis | |
| DeepLabCut-RESNET-101 | - | Pretraining boosts out-of-domain robustness for pose estimation | |
| DeepLabCut-MOBILENETV2 0.35 | - | Pretraining boosts out-of-domain robustness for pose estimation | |
| DeepLabCut-RESNET 50 | - | Pretraining boosts out-of-domain robustness for pose estimation |
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