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

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

10 April 2018

Dongsheng Li

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

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Title
Focal Loss for Dense Object Detection Nayeon Lee Priya Goyal Ross B. Girshick Kaiming He Piotr Dollár ObjD 132 3,001 0 07 Aug 2017
Design of Efficient Convolutional Layers using Single Intra-channel Convolution, Topological Subdivisioning and Spatial "Bottleneck" Structure Min Wang Baoyuan Liu H. Foroosh 57 51 0 15 Aug 2016
R-FCN: Object Detection via Region-based Fully Convolutional Networks Jifeng Dai Yi Li Kaiming He Jian Sun ObjD 185 5,650 0 20 May 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 165 7,503 0 24 Feb 2016
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun ObjD 416 11,242 0 18 Jun 2014