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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