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Keyword: class activation mapping ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Res2Net: A New Multi-Scale Backbone Architecture

   Gao, Cheng, Zhao, Zhang, Yang and Torr · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2019

   The paper proposes Res2Net, a building block for convolutional networks that adds hierarchical residual-like connections inside one residual block, and reports performance gains over baselines on several vision tasks.

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   1. UncheckedThe paper says Res2Net represents multi-scale features within a single layer and widens the range of receptive fields at each network layer.“The Res2Net represents multi-scale features at a granular level and increases the range of receptive fields for each network layer.”
   2. UncheckedAdding the Res2Net block to several standard image-recognition networks gave consistent gains over the original versions on datasets such as CIFAR-100 and ImageNet.“We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e.g., CIFAR-100 and ImageNet.”