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Multi-scale Location-Aware Kernel Representation for Object Detection
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Although Faster R-CNN and its variants have shown promising performance in object detection, they only exploit simple first-order representation of object proposals for final classification and regression. Recent classification methods demonstrate that the integration of highorder statistics into deep convolutional neural networks can achieve impressive improvement, but their goal is to model whole images by discarding location information so that they cannot be directly adopted to object
doi:10.1109/cvpr.2018.00136
dblp:conf/cvpr/WangWGLZ18
fatcat:4s7mbdxpezcadn5kih4v2vsl7u