Research Article
SAL-Net: Self-Supervised Attribute Learning for Object Recognition and Segmentation
Table 1
Effectiveness of the proposed strategies, including multitask learning, features from multiple CNN layers, and joint learning with attributes.
| Model | Strategies | CUB-2011 [10] | Pascal VOC [28] | Multitask | Multifeature | Attribute learning | Acc (%) | aIoU (%) | Acc (%) | aIoU (%) |
| ST-cls | | | | 64.67 | — | 67.46 | — | ST-seg | | | | — | 79.76 | — | 73.81 | MT-SF | ✓ | | | 70.37 | 74.22 | 69.11 | 74.02 | MT-MF | ✓ | ✓ | | 71.45 | 82.61 | 71.42 | 77.59 | AFE-Net [27] | ✓ | ✓ | ✓ | 74.37 | 85.07 | — | — | SAL-Net (ours) | ✓ | ✓ | ✓ | 77.55 | 86.66 | 75.00 | 78.19 |
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