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20192022
most citedPP-LCNet: A Lightweight CPU Convolutional Neural Network

97 citations · 233 across the 9 of their papers we have counts for

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9 papers · 1 filter

cs.CV20222 cited

2nd Place Solution to Google Landmark Retrieval 2020

Min Yang, Cheng Cui, Xuetong Xue +2

This paper presents the 2nd place solution to the Google Landmark Retrieval Competition 2020. We propose a training method of global feature model for landmark retrieval without po…

cs.CV202192 cited

PP-PicoDet: A Better Real-Time Object Detector on Mobile Devices

Guanghua Yu, Qinyao Chang, Wenyu Lv +12

The better accuracy and efficiency trade-off has been a challenging problem in object detection. In this work, we are dedicated to studying key optimizations and neural network arc…

cs.CV202126 cited

PP-OCRv2: Bag of Tricks for Ultra Lightweight OCR System

Yuning Du, Chenxia Li, Ruoyu Guo +9

Optical Character Recognition (OCR) systems have been widely used in various of application scenarios. Designing an OCR system is still a challenging task. In previous work, we pro…

cs.CV202197 cited

PP-LCNet: A Lightweight CPU Convolutional Neural Network

Cheng Cui, Tingquan Gao, Shengyu Wei +10

We propose a lightweight CPU network based on the MKLDNN acceleration strategy, named PP-LCNet, which improves the performance of lightweight models on multiple tasks. This paper l…

cs.CV20213 cited

Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones

Cheng Cui, Ruoyu Guo, Yuning Du +10

Recently, research efforts have been concentrated on revealing how pre-trained model makes a difference in neural network performance. Self-supervision and semi-supervised learning…

cs.CV2020

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

Pengcheng Yuan, Shufei Lin, Cheng Cui +5

This paper addresses representational block named Hierarchical-Split Block, which can be taken as a plug-and-play block to upgrade existing convolutional neural networks, improves…