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20172025
most citedCorrelation Congruence for Knowledge Distillation

3 citations · 3 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.CV2021

Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment

Baoyun Peng, Min Liu, Zhaoning Zhang +2

Face recognition has made significant progress in recent years due to deep convolutional neural networks (CNN). In many face recognition (FR) scenarios, face images are acquired fr…

cs.CV2019★ 3 cited

Correlation Congruence for Knowledge Distillation

Baoyun Peng, Xiao Jin, Jiaheng Liu +5

Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between…

cs.CV2019

ThunderNet: Towards Real-time Generic Object Detection

Zheng Qin, Zeming Li, Zhaoning Zhang +4

Real-time generic object detection on mobile platforms is a crucial but challenging computer vision task. However, previous CNN-based detectors suffer from enormous computational c…

cs.CV2018

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

Hao Yu, Zhaoning Zhang, Zheng Qin +4

Modern object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those pr…

cs.CV2018

Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions

Zheng Qin, Zhaoning Zhang, Dongsheng Li +2

Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds. However, training depthwise convolution layers with GPUs is…

cs.CV2018

Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications

Zheng Qin, Zhaoning Zhang, Shiqing Zhang +2

Compact neural networks are inclined to exploit "sparsely-connected" convolutions such as depthwise convolution and group convolution for employment in mobile applications. Compare…