Pose Estimation On Ochuman
Metriken
Test AP
Validation AP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Test AP | Validation AP |
|---|---|---|
| associative-embedding-end-to-end-learning-for | 29.5 | 32.1 |
| rethinking-pose-estimation-in-crowds | 47.2 | 47.7 |
| vitpose-simple-vision-transformer-baselines | 93.3 | 92.8 |
| rtmpose-real-time-multi-person-pose | 80.3 | 80.5 |
| you-only-learn-one-query-learning-unified | 40.0 | - |
| you-only-learn-one-query-learning-unified | 45.6 | - |
| differentiable-hierarchical-graph-grouping | 36.0 | 41.8 |
| contextual-instance-decoupling-for-robust | 45.0 | 46.1 |
| simple-baselines-for-human-pose-estimation | 33.3 | 41.0 |
| simple-baselines-for-human-pose-estimation | 29.5 | 32.1 |
| detection-pose-estimation-and-segmentation-1 | 48.3 | 48.6 |
| transpose-towards-explainable-human-pose | - | 62.3 |
| associative-embedding-end-to-end-learning-for | 32.8 | 40.0 |
| multi-hypothesis-pose-networks-rethinking-top | 42.5 | 42.0 |
| rmpe-regional-multi-person-pose-estimation | 30.7 | 38.8 |
| detection-pose-estimation-and-segmentation-1 | 45.0 | 45.3 |
| unihcp-a-unified-model-for-human-centric | 87.4 | - |
| multi-hypothesis-pose-networks-rethinking-top | 37.2 | 37.8 |