Detailed explanation of RepLKNet paper: 31×31 super large convolution kernel model - Code World

Detailed explanation of RepLKNet paper: 31×31 super large convolution kernel model

Enterprise 2023-04-10 02:42:08 views: null

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Origin blog.csdn.net/Zosse/article/details/127024471

Detailed explanation of RepLKNet paper: 31×31 super large convolution kernel model

CVPR 2022 | The convolution kernel is as large as 31x31! Ups and downs and efficient! Tsinghua & Megvii proposed RepLKNet: a new visual backbone network...

Tsinghua and Megvii proposed RepLKNet: a CNN network with a large kernel of 31×31, which has better performance than Swin

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YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.84] are integrated into the 2023 latest large convolution kernel CNN architecture RepLKNet upgraded version-UniRepLKNet

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