Pose Estimation On Coco Val2017
평가 지표
AP
AR
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | AP | AR | Paper Title | Repository |
---|---|---|---|---|
MogaNet-S (256x192) | 74.9 | 80.1 | MogaNet: Multi-order Gated Aggregation Network | |
MogaNet-T (256x192) | 73.2 | 78.8 | MogaNet: Multi-order Gated Aggregation Network | |
ViTPose-B (Single-task_GT-bbox_256x192) | 77.3 | 80.4 | ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation | |
Bias (HRNet_256x192) | 75.8 | - | Removing the Bias of Integral Pose Regression | - |
HRNet (256x192) | 75.3 | - | Deep High-Resolution Representation Learning for Human Pose Estimation | |
MogaNet-B (384x288) | 77.3 | 82.2 | MogaNet: Multi-order Gated Aggregation Network | |
SimpleBaseLine (256x192) | 70.4 | - | Simple Baselines for Human Pose Estimation and Tracking | |
MogaNet-S (384x288) | 76.4 | 81.4 | MogaNet: Multi-order Gated Aggregation Network | |
CCNet (ViTPose-B_GT-bbox_256x192) | 78.1 | 80.4 | On the Calibration of Human Pose Estimation | - |
ViTPose-B (Single-task_Det-bbox_256x192) | 75.8 | 81.1 | ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation | |
RLE (256x192) | 71.3 | - | Human Pose Regression with Residual Log-likelihood Estimation |
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