Action Classification On Toyota Smarthome
评估指标
CS
CV1
CV2
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | CS | CV1 | CV2 |
|---|---|---|---|
| vpn-learning-video-pose-embedding-for | 60.8 | 43.8 | 53.5 |
| mmnet-a-model-based-multimodal-network-for | 70.1 | - | - |
| improved-dense-trajectory-with-cross-streams | 41.9 | 20.9 | 23.7 |
| toyota-smarthome-real-world-activities-of | 54.2 | 35.2 | 50.3 |
| just-add-p-pose-induced-video-transformers | 72.9 | 55.2 | 64.8 |
| quo-vadis-action-recognition-a-new-model-and | 53.4 | 34.9 | 45.1 |
| recognizing-actions-in-videos-from-unseen | - | 39.6 | 54.6 |
| proformer-learning-data-efficient | - | - | - |
| unik-a-unified-framework-for-real-world | 64.3 | 36.1 | 65.0 |
| adaptive-intermediate-representations-for | 62.11 | - | - |
| non-local-neural-networks | 53.6 | 34.3 | 43.9 |
| assemblenet-assembling-modality | 63.6 | - | - |