Prompt Engineering On Ucf101
Métriques
Harmonic mean
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Harmonic mean |
|---|---|
| promptkd-unsupervised-prompt-distillation-for | 86.10 |
| learning-domain-invariant-prompt-for-vision | 81.35 |
| maple-multi-modal-prompt-learning | 80.82 |
| self-regulating-prompts-foundational-model | 82.74 |
| learning-hierarchical-prompt-with-structured | 83.16 |
| mmrl-multi-modal-representation-learning-for | 83.89 |
| consistency-guided-prompt-learning-for-vision | 83.07 |
| prompt-learning-via-meta-regularization | 83.25 |
| learning-transferable-visual-models-from | 73.85 |
| hpt-hierarchically-prompting-vision-language | 83.81 |
| conditional-prompt-learning-for-vision | 77.64 |
| read-only-prompt-optimization-for-vision | 79.34 |
| dept-decoupled-prompt-tuning | 82.46 |