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Weakly Supervised Object Localization On Cub

Metrics

MaxBoxAccV2
Top-1 Error Rate

Results

Performance results of various models on this benchmark

Paper Title
ADL66.337.71Attention-based Dropout Layer for Weakly Supervised Object Localization
InfoCAM-54.17Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator
F-CAM80.1-F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling
PSOL-DenseNet161-Sep--Rethinking the Route Towards Weakly Supervised Object Localization
ART-34.8Attributional Robustness Training using Input-Gradient Spatial Alignment
LOST--Localizing Objects with Self-Supervised Transformers and no Labels
TokenCut--Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
GenPromp--Generative Prompt Model for Weakly Supervised Object Localization
DiPS90.9-Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localization
SPG60.453.36Self-produced Guidance for Weakly-supervised Object Localization
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Weakly Supervised Object Localization On Cub | SOTA | HyperAI