基于深度学习的目标检测发展历程:deep_learning_object_detection

目标检测论文从 2014-2018

模型表现表格

Detector	VOC07 (mAP@IoU=0.5)	VOC12 (mAP@IoU=0.5)	COCO (mAP)	Published In
R-CNN	58.5	–	–	CVPR’14
OverFeat	–	–	–	ICLR’14
MultiBox	29.0	–	–	CVPR’14
SPP-Net	59.2	–	–	ECCV’14
MR-CNN	78.2 (07+12)	73.9 (07+12)	–	ICCV’15
AttentionNet	–	–	–	ICCV’15
Fast R-CNN	70.0 (07+12)	68.4 (07++12)	–	ICCV’15
Faster R-CNN	73.2 (07+12)	70.4 (07++12)	–	NIPS’15
YOLO v1	66.4 (07+12)	57.9 (07++12)	–	CVPR’16
G-CNN	66.8	66.4 (07+12)	–	CVPR’16
AZNet	70.4	–	22.3	CVPR’16
ION	80.1	77.9	33.1	CVPR’16
HyperNet	76.3 (07+12)	71.4 (07++12)	–	CVPR’16
OHEM	78.9 (07+12)	76.3 (07++12)	22.4	CVPR’16
MPN	–	–	33.2	BMVC’16
SSD	76.8 (07+12)	74.9 (07++12)	–	ECCV’16
GBDNet	77.2 (07+12)	–	27.0	ECCV’16
CPF	76.4 (07+12)	72.6 (07++12)	–	ECCV’16
MS-CNN	–	–	–	ECCV’16
R-FCN	79.5 (07+12)	77.6 (07++12)	29.9	NIPS’16
PVANET	–	–	–	NIPSW’16
DeepID-Net	69.0	–	–	PAMI’16
NoC	71.6 (07+12)	68.8 (07+12)	27.2	TPAMI’16
DSSD	81.5 (07+12)	80.0 (07++12)	–	arXiv’17
TDM	–	–	37.3	CVPR’17
FPN	–	–	36.2	CVPR’17
YOLO v2	78.6 (07+12)	73.4 (07++12)	–	CVPR’17
RON	77.6 (07+12)	75.4 (07++12)	–	CVPR’17
DCN	–	–	–	ICCV’17
DeNet	77.1 (07+12)	73.9 (07++12)	33.8	ICCV’17
CoupleNet	82.7 (07+12)	80.4 (07++12)	34.4	ICCV’17
RetinaNet	–	–	39.1	ICCV’17
Mask R-CNN	–	–	–	ICCV’17
DSOD	77.7 (07+12)	76.3 (07++12)	–	ICCV’17
SMN	70.0	–	–	ICCV’17
YOLO v3	–	–	33.0	Arxiv’18
SIN	76.0 (07+12)	73.1 (07++12)	23.2	CVPR’18
STDN	80.9 (07+12)	–	–	CVPR’18
RefineDet	83.8 (07+12)	83.5 (07++12)	41.8	CVPR’18
MegDet	–	–	–	CVPR’18
RFBNet	82.2 (07+12)	–	–	ECCV’18

论文列表：https://github.com/hoya012/deep_learning_object_detection

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