Graph-propagation based Correlation Learning for Weakly Supervised Fine-grained Image Classification

AAAI-2020 2020 Zhihui WangShijie WangHaojie LiZhi DouJianjun Li

The key of Weakly Supervised Fine-grained Image Classification (WFGIC) is how to pick out the discriminative regions and learn the discriminative features from them. However, most recent WFGIC methods pick out the discriminative regions independently and utilize their features directly, while neglecting the facts that regions’ features are mutually semantic correlated and region groups can be more discriminative... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Fine-Grained Image Classification CUB-200-2011 GCL Accuracy 88.3% # 14
Fine-Grained Image Classification FGVC Aircraft GCL Accuracy 93.2% # 8
Fine-Grained Image Classification Stanford Cars GCL Accuracy 94.0% # 13

Methods used in the Paper


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