Before revision:  In this paper, we utilize a linearized attention function to overcome above problems and build a novel architecture , named Content-Augmented Feature Pyramid Network (CA-FPN) , which proposes a global content extraction module and deeply combines with FPN through light linear transformers.
After revision:  In this paper, we utilize a linearized attention function to overcome above problems and build a novel architecture , named Content-Augmented Feature Pyramid Network (CA-FPN) . Unlike the vanilla FPN, which fuses features within a local receptive field, CA-FPN can adaptively aggregate similar features from a global view. It is equipped with a global content extraction module and deeply combines with FPN through light linear transformers.