Web: http://arxiv.org/abs/2206.06637

June 16, 2022, 1:13 a.m. | Shanghua Gao, Zhong-Yu Li, Qi Han, Ming-Ming Cheng, Liang Wang

cs.CV updates on arXiv.org arxiv.org

Temporal/spatial receptive fields of models play an important role in
sequential/spatial tasks. Large receptive fields facilitate long-term
relations, while small receptive fields help to capture the local details.
Existing methods construct models with hand-designed receptive fields in
layers. Can we effectively search for receptive field combinations to replace
hand-designed patterns? To answer this question, we propose to find better
receptive field combinations through a global-to-local search scheme. Our
search scheme exploits both global search to find the coarse combinations and …

arxiv convolutional neural networks cv networks neural neural networks search

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