Code is available at: https://github.com/weiliu89/caffe/tree/ssd . Wei Liu, et al., "SSD: Single Shot MultiBox Detector" https://arxiv.org/abs/1512.02325 物体検出タスクにおいて、YOLOよりも高速でしかもFaster R-CNNと同等の精度を実現したSSDの…

Compared to other single stage methods, SSD has much better accuracy even with a smaller input image size. Wei Liu, et al., "SSD: Single Shot MultiBox Detector" https://arxiv.org/abs/1512.02325 物体検出タスクにおいて、YOLOよりも高速でしか…

For 300 × 300 input, SSD achieves 74.3% mAP on VOC2007 test at 59 FPS on a Nvidia Titan X and for 512 × 512 input, SSD achieves 76.9% mAP, outperforming a comparable state-of-the-art Faster R-CNN model. Wei Liu, et al., "SSD: Single Shot M…

Experimental results on the PASCAL VOC, COCO, and ILSVRC datasets confirm that SSD has competitive accuracy to methods that utilize an additional object proposal step and is much faster, while providing a unified framework for both trainin…

This makes SSD easy to train and straightforward to integrate into systems that require a detection component. Wei Liu, et al., "SSD: Single Shot MultiBox Detector" https://arxiv.org/abs/1512.02325 物体検出タスクにおいて、YOLOよりも高速で…

SSD is simple relative to methods that require object proposals because it completely eliminates proposal generation and subsequent pixel or feature resampling stages and encapsulates all computation in a single network. Wei Liu, et al., "…