# For 'voc_2007_test' and 'coco_2014_minival', it will directly output the mAP results. # - coco_path: where the trained voc caffemodel. # - voc_path: where the trained voc caffemodel. # You can modify the parameters in refinedet_test.py for different types of evaluation: # - single_scale: True is single scale testing, False is multi_scale_testing. Please cite our paper in your publications if it helps your research: The code of the multi-scale testing has also been released in this repository. Note: RefineDet300+ and RefineDet512+ are evaluated with the multi-scale testing strategy. For more details, please refer to our paper. You can use the code to train/evaluate the RefineDet method for object detection. We propose a novel single-shot based detector, called RefineDet, that achieves better accuracy than two-stage methods and maintains comparable efficiency of one-stage methods. Single-Shot Refinement Neural Network for Object Detectionīy Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, Stan Z.
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