Image Captioning On Nocaps Xd Entire
评估指标
B1
B2
B3
B4
CIDEr
METEOR
ROUGE-L
SPICE
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 | B1 | B2 | B3 | B4 | CIDEr | METEOR | ROUGE-L | SPICE |
|---|---|---|---|---|---|---|---|---|
| 模型 1 | 72.33 | 52.42 | 30.83 | 14.73 | 53.36 | 21.52 | 48.87 | 9.15 |
| scaling-up-vision-language-pre-training-for | 85.62 | 71.36 | 53.62 | 34.65 | 114.25 | 31.27 | 61.2 | 14.85 |
| 模型 3 | 76.64 | 56.46 | 36.37 | 19.48 | 85.34 | 28.15 | 52.83 | 14.67 |
| 模型 4 | 79.17 | 60.29 | 39.06 | 20.81 | 85.02 | 26.54 | 53.39 | 12.74 |
| git-a-generative-image-to-text-transformer | 88.1 | 74.81 | 57.68 | 37.35 | 123.39 | 32.5 | 63.12 | 15.94 |
| 模型 6 | 76.59 | 56.74 | 35.39 | 18.41 | 73.09 | 24.42 | 51.82 | 11.2 |
| git-a-generative-image-to-text-transformer | 88.43 | 75.02 | 57.87 | 37.65 | 124.77 | 32.56 | 63.19 | 16.06 |
| 模型 8 | 74.0 | 55.11 | 35.23 | 19.16 | 54.25 | 22.96 | 50.92 | 10.14 |
| 模型 9 | 73.42 | 52.12 | 29.35 | 12.88 | 61.48 | 22.06 | 48.74 | 9.69 |
| 模型 10 | 78.77 | 61.54 | 41.85 | 23.77 | 85.3 | 25.96 | 54.59 | 11.84 |
| vivo-surpassing-human-performance-in-novel | 82.27 | 66.04 | 47.48 | 28.95 | 100.12 | 29.47 | 58.26 | 14.04 |
| 模型 12 | 83.69 | 67.96 | 49.38 | 29.69 | 102.39 | 29.68 | 58.99 | 14.71 |