Action Recognition on HMDB (Top-1 Accuracy)
75.9Top-1 AccuracyS3D (supervised learning)
Evaluation Results
| Method | Links | |
|---|---|---|
| S3D (supervised learning)Model (Backbone)=S3D, Frozen=✖2022.03 | 75.9 | |
| VT-TWINSPre-training Dataset=HTM, MM (Modality)=Text, Model (Backbone)=S3D, Frozen=✔2022.03 | 57.9 | |
| MIL-NCEPre-training Dataset=HTM, MM (Modality)=Text, Model (Backbone)=I3D, Frozen=✔2022.03 | 54.8 | |
| MIL-NCEPre-training Dataset=HTM, MM (Modality)=Text, Model (Backbone)=S3D, Frozen=✔2022.03 | 53.1 | |
| AVTSPre-training Dataset=K600, MM (Modality)=Audio, Model (Backbone)=I3D, Frozen=✖2022.03 | 53 | |
| CBTPre-training Dataset=K600, MM (Modality)=✖, Model (Backbone)=S3D, Frozen=✖2022.03 | 44.6 | |
| 3DRotNetPre-training Dataset=K600, MM (Modality)=✖, Model (Backbone)=S3D, Frozen=✖2022.03 | 40 | |
| Shuffle & LearnPre-training Dataset=K600, MM (Modality)=✖, Model (Backbone)=S3D, Frozen=✖2022.03 | 35.8 | |
| DPCPre-training Dataset=K400, MM (Modality)=✖, Model (Backbone)=3D-R34, Frozen=✖2022.03 | 35.7 | |
| 3D ST-puzzlePre-training Dataset=K400, MM (Modality)=✖, Model (Backbone)=3D-R18, Frozen=✖2022.03 | 33.7 | |
| Wang et al.Pre-training Dataset=K400, MM (Modality)=Flow, Model (Backbone)=C3D, Frozen=✖2022.03 | 33.4 | |
| Fernanado et al.Pre-training Dataset=UCF, MM (Modality)=✖, Model (Backbone)=AlexNet, Frozen=✖2022.03 | 32.5 | |
| ClipOrderPre-training Dataset=UCF, MM (Modality)=✖, Model (Backbone)=R(2+1)D, Frozen=✖2022.03 | 30.9 | |
| CBTPre-training Dataset=K600, MM (Modality)=✖, Model (Backbone)=S3D, Frozen=✔2022.03 | 29.5 | |
| CMCPre-training Dataset=UCF, MM (Modality)=Flow, Model (Backbone)=CaffeNet, Frozen=✖2022.03 | 26.7 | |
| GeometryPre-training Dataset=UCF, MM (Modality)=Flow, Model (Backbone)=CaffeNet, Frozen=✖2022.03 | 26.7 | |
| OPNPre-training Dataset=UCF, MM (Modality)=✖, Model (Backbone)=VGG, Frozen=✖2022.03 | 23.8 |