Image Classification On Places205
评估指标
Top 1 Accuracy
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 | Top 1 Accuracy |
|---|---|
| mixmim-mixed-and-masked-image-modeling-for | 69.3 |
| self-supervised-pretraining-of-visual | 66.0 |
| automix-unveiling-the-power-of-mixup | 64.1 |
| masked-autoencoders-are-scalable-vision | 66.8 |
| internimage-exploring-large-scale-vision | 71.7% |
| unsupervised-learning-of-visual-features-by | 56.7% |
| boosting-discriminative-visual-representation | 64.3 |
| mixmim-mixed-and-masked-image-modeling-for | 68.3 |
| unsupervised-learning-of-visual-features-by | 53.2% |
| barlow-twins-self-supervised-learning-via | 54.1% |
| improved-baselines-with-momentum-contrastive | 52.9 |
| vision-models-are-more-robust-and-fair-when | 69.0 |
| bootstrap-your-own-latent-a-new-approach-to | 54.0 |
| self-supervised-pretraining-of-visual | 62.7 |
| a-simple-framework-for-contrastive-learning | 53.3 |