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

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Origin blog.csdn.net/amusi1994/article/details/123516508

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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RepLKNet：不是大卷积不好，而是卷积不够大，31x31卷积了解一下 | CVPR 2022

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CVPR 2022 |畳み込みカーネルは31x31と同じ大きさです！浮き沈みと効率的！Tsinghua＆MegviiはRepLKNetを提案しました：新しいビジュアルバックボーンネットワーク...

CVPR 2022 | 컨볼루션 커널은 최대 31x31입니다! 기복과 효율성! Tsinghua & Megvii는 새로운 시각적 백본 네트워크인 RepLKNet을 제안했습니다...

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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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CVPR 2022 | CNN Self-Supervised Pre-training New SOTA! Shanghai Jiao et al. jointly proposed HCSC: a new framework for image representation self-learning with hierarchical structure...

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