Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization

CVPR 2018 Peihua LiJiangtao XieQilong WangZilin Gao

Global covariance pooling in convolutional neural networks has achieved impressive improvement over the classical first-order pooling. Recent works have shown matrix square root normalization plays a central role in achieving state-of-the-art performance... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Fine-Grained Image Classification CUB-200-2011 MPN-COV Accuracy 88.7% # 10
Fine-Grained Image Classification CUB-200-2011 MPN-COV Accuracy 88.7 # 2
Fine-Grained Image Classification FGVC Aircraft MPN-COV Accuracy 91.4% # 18
Fine-Grained Image Classification Stanford Cars MPN-COV Accuracy 93.3% # 16

Methods used in the Paper


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