A Unified Multi scale Deep Convolutional Neural Network for Fast Object Detection
A unified deep neural network, denoted the multi scale CNN (MS CNN) is proposed for fast multi scale object detection. The MS CNN consists of a proposal sub network and a detection sub network. In the proposal sub network, detection is performed at multiple output layers, so that receptive fields match objects of different scales. These complementary scale specific detectors are combined to produce a strong multi scale object detector. The unified network is learned end to end, by optimizing a multi task loss. Feature upsampling by deconvolution is also explored, as an alternative to input upsampling, to reduce the memory and computation costs. State of the art object detection performance, at up to 15 fps, is reported on datasets, such as KITTI and Caltech, containing a substantial number of small objects.
ECCV