no code implementations • 9 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.
2 code implementations • ICCV 2019 • Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yi-Chao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang
Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level.
4 code implementations • 28 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.
Ranked #14 on Object Detection on PASCAL VOC 2007
no code implementations • 10 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.
3 code implementations • 27 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.
2 code implementations • 24 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.
2 code implementations • 11 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.
no code implementations • 5 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.