Weakly-supervised object localization on CUB-200 2011 (test)
96.54AccuracyWWbL
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| WWbLBackbone=Resnet502022.06 | 96.54 | — | — | |
| SPOLBackbone=Resnet502022.06 | 96.46 | — | — | |
| BASBackbone=Resnet502022.06 | 95.13 | — | — | |
| WWbLBackbone=MobileNetV12022.06 | 94.4 | — | — | |
| WWbLBackbone=InceptionV32022.06 | 94.3 | — | — | |
| WWbLBackbone=VGG162022.06 | 93.94 | — | — | |
| WWbLBackbone=DenseNet1612022.06 | 93.71 | — | — | |
| PSOLBackbone=DenseNet1612022.06 | 93.01 | — | — | |
| BASBackbone=MobileNetV12022.06 | 92.35 | — | — | |
| BASBackbone=InceptionV32022.06 | 92.24 | — | — | |
| BASBackbone=VGG162022.06 | 91.07 | — | — | |
| POSLBackbone=Resnet502022.06 | 90 | — | — | |
| FAMBackbone=VGG162022.06 | 89.26 | — | — | |
| POSLBackbone=VGG162022.06 | 89.11 | — | — | |
| SLTBackbone=VGG162022.06 | 87.6 | — | — | |
| FAMBackbone=InceptionV32022.06 | 87.25 | — | — | |
| SLTBackbone=InceptionV32022.06 | 86.5 | — | — | |
| ORNetBackbone=VGG162022.06 | 86.2 | — | — | |
| FAMBackbone=Resnet502022.06 | 85.73 | — | — | |
| FAMBackbone=MobileNetV12022.06 | 85.71 | — | — | |
| GCNetBackbone=VGG162022.06 | 81.1 | — | — | |
| RCAMBackbone=MobileNetV12022.06 | 78.6 | — | — | |
| WTLBackbone=Resnet502022.06 | 77.35 | — | — | |
| SPABackbone=VGG162022.06 | 77.29 | — | — | |
| ADLBackbone=VGG162022.06 | 75.41 | — | — | |
| GCNetBackbone=InceptionV32022.06 | 75.3 | — | — | |
| MEILBackbone=VGG162022.06 | 73.84 | — | — | |
| I2CBackbone=InceptionV32022.06 | 72.6 | — | — | |
| SPABackbone=InceptionV32022.06 | 72.14 | — | — | |
| GAEBackbone=CLIP2022.06 | 68.01 | — | — | |
| DANetBackbone=VGG162022.06 | 67.7 | — | — | |
| HaSBackbone=MobileNetV12022.06 | 67.31 | — | — | |
| DANetBackbone=InceptionV32022.06 | 67.03 | — | — | |
| CAMBackbone=MobileNetV12022.06 | 63.3 | — | — | |
| ACOLBackbone=VGG162022.06 | 62.96 | — | — | |
| CAMBackbone=Resnet502022.06 | 57.35 | — | — | |
| CAMBackbone=VGG162022.06 | 55.1 | — | — | |
| CAMBackbone=InceptionV32022.06 | 55.1 | — | — | |
| GoogLeNet-GAPbackbone=GoogLeNet2019.05 | — | 59 | — | |
| MAANspatial aggregation size=4x42019.05 | — | 55.9 | 47.6 | |
| MAANspatial aggregation size=7x72019.05 | — | 53.94 | 44.13 | |
| weighted-CAMspatial aggregation size=4x42019.05 | — | 58.51 | 51.73 | |
| weighted-CAMspatial aggregation size=7x72019.05 | — | 58.11 | 50.21 |