Human Instance Segmentation On Ochuman
Metriken
AP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | AP |
|---|---|
| count-and-similarity-aware-r-cnn-for | 18.0 |
| you-only-learn-one-query-learning-unified | 31.1 |
| real-time-human-centric-segmentation-for | 23.4 |
| real-time-human-centric-segmentation-for | 29.8 |
| crowd-sam-sam-as-a-smart-annotator-for-object | 31.4 |
| poseg-pose-aware-refinement-network-for-human | 26.4 |
| detection-pose-estimation-and-segmentation-1 | 26.5 |
| poseg-pose-aware-refinement-network-for-human | 26.8 |
| object-centric-multi-task-learning-for-human | 27.8 |
| object-centric-multi-task-learning-for-human | 27.3 |
| count-and-similarity-aware-r-cnn-for | 16.9 |
| object-centric-multi-task-learning-for-human | 25.5 |
| test-time-adaptation-vs-training-time | 22.42 |
| pose2seg-detection-free-human-instance | 23.8 |
| humans-need-not-label-more-humans-occlusion | 28.3 |
| occlusion-aware-instance-segmentation-via | 20.6 |
| real-time-human-centric-segmentation-for | 28.1 |
| detection-pose-estimation-and-segmentation-1 | 32.4 |
| you-only-learn-one-query-learning-unified | 38.8 |