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Image Captioning On Flickr30K Captions Test
評価指標
CIDEr
SPICE
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
| Paper Title | |||
|---|---|---|---|
| Unified VLP | 67.4 | 17 | Unified Vision-Language Pre-Training for Image Captioning and VQA |
| KOSMOS-1 1.6B (zero-shot) | 67.1 | 14.5 | - |
| Cornia et al | 46.4 | - | Paying More Attention to Saliency: Image Captioning with Saliency and Context Attention |
| MetaLM | 43.3 | 11.7 | Language Models are General-Purpose Interfaces |
| FewVLM | 31.0 | 10.0 | A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models |
| BRNN | 24.7 | - | Deep Visual-Semantic Alignments for Generating Image Descriptions |
| VL-T5 | 2.6 | 2.0 | Unifying Vision-and-Language Tasks via Text Generation |
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