Object Counting On Tallyqa Complex
Métriques
Accuracy
RMSE
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | RMSE | Paper Title | Repository |
|---|---|---|---|---|
| MoVie-ResNeXt | 56.8 | 1.43 | MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond | |
| RCN | 56.2 | 1.43 | TallyQA: Answering Complex Counting Questions | |
| PaLI-X-VPD | 76.6 | - | Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models | - |
| SMoLA-PaLI-X Specialist | 77.1 | - | Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts | - |
| MoVie | 54.1 | 1.52 | MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond | |
| SMoLA-PaLI-X Generalist (0 shot) | 70.7 | - | Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts | - |
0 of 6 row(s) selected.