CARAFE++: Unified Content-Aware ReAssembly of FEatures

@article{Wang2022CARAFEUC,
  title={CARAFE++: Unified Content-Aware ReAssembly of FEatures},
  author={Jiaqi Wang and Kai Chen and Rui Xu and Ziwei Liu and Chen Change Loy and Dahua Lin},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2022},
  volume={44},
  pages={4674-4687}
}
  • Jiaqi WangKai Chen Dahua Lin
  • Published 7 December 2020
  • Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature reassembly, i.e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e.g., residual networks and feature pyramids. Its design is critical for dense prediction tasks such as object detection and semantic/instance segmentation. In this work, we propose unified Content-Aware ReAssembly of FEatures (CARAFE++), a universal, lightweight, and highly effective operator to fulfill this goal. CARAFE++ has several appealing properties… 

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