Search Results for author: Zhaoning Zhang

Found 8 papers, 5 papers with code

Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment

no code implementations9 Jun 2021 Baoyun Peng, Min Liu, Heng Yang, Zhaoning Zhang, Dongsheng Li

Based on the proposed quality measurement, we propose a deep Tiny Face Quality network (tinyFQnet) to learn a quality prediction function from data.

Face Recognition Image Quality Assessment

ThunderNet: Towards Real-time Generic Object Detection

4 code implementations28 Mar 2019 Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, Jian Sun

In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.

object-detection Object Detection

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

no code implementations10 Apr 2018 Hao Yu, Zhaoning Zhang, Zheng Qin, Hao Wu, Dongsheng Li, Jun Zhao, Xicheng Lu

LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples.

Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions

3 code implementations27 Mar 2018 Zheng Qin, Zhaoning Zhang, Dongsheng Li, Yiming Zhang, Yuxing Peng

Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds.

Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications

2 code implementations24 Mar 2018 Zheng Qin, Zhaoning Zhang, Shiqing Zhang, Hao Yu, Yuxing Peng

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

FD-MobileNet: Improved MobileNet with a Fast Downsampling Strategy

2 code implementations11 Feb 2018 Zheng Qin, Zhaoning Zhang, Xiaotao Chen, Yuxing Peng

Experiments on ILSVRC 2012 and PASCAL VOC 2007 datasets demonstrate that FD-MobileNet consistently outperforms MobileNet and achieves comparable results with ShuffleNet under different computational budgets, for instance, surpassing MobileNet by 5. 5% on the ILSVRC 2012 top-1 accuracy and 3. 6% on the VOC 2007 mAP under a complexity of 12 MFLOPs.

S-OHEM: Stratified Online Hard Example Mining for Object Detection

no code implementations5 May 2017 Minne Li, Zhaoning Zhang, Hao Yu, Xinyuan Chen, Dongsheng Li

S-OHEM exploits OHEM with stratified sampling, a widely-adopted sampling technique, to choose the training examples according to this influence during hard example mining, and thus enhance the performance of object detectors.

object-detection Object Detection

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