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hoya012/deep_learning_object_detection: A paper list of object detection using d ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称：

hoya012/deep_learning_object_detection

开源软件地址：

https://github.com/hoya012/deep_learning_object_detection

开源编程语言：

Python 100.0%

开源软件介绍：

deep learning object detection

A paper list of object detection using deep learning. I wrote this page with reference to this survey paper and searching and searching..

Last updated: 2020/09/22

Update log

2018/9/18 - update all of recent papers and make some diagram about history of object detection using deep learning. 2018/9/26 - update codes of papers. (official and unofficial)
2018/october - update 5 papers and performance table.
2018/november - update 9 papers.
2018/december - update 8 papers and and performance table and add new diagram(2019 version!!).
2019/january - update 4 papers and and add commonly used datasets.
2019/february - update 3 papers.
2019/march - update figure and code links.
2019/april - remove author's names and update ICLR 2019 & CVPR 2019 papers.
2019/may - update CVPR 2019 papers.
2019/june - update CVPR 2019 papers and dataset paper.
2019/july - update BMVC 2019 papers and some of ICCV 2019 papers.
2019/september - update NeurIPS 2019 papers and ICCV 2019 papers.
2019/november - update some of AAAI 2020 papers and other papers.
2020/january - update ICLR 2020 papers and other papers.
2020/may - update CVPR 2020 papers and other papers.
2020/june - update arxiv papers.
2020/august - update paper links.

Table of Contents

Paper list from 2014 to now(2019)

The part highlighted with red characters means papers that i think "must-read". However, it is my personal opinion and other papers are important too, so I recommend to read them if you have time.

Performance table

FPS(Speed) index is related to the hardware spec(e.g. CPU, GPU, RAM, etc), so it is hard to make an equal comparison. The solution is to measure the performance of all models on hardware with equivalent specifications, but it is very difficult and time consuming.

Detector VOC07 (mAP@IoU=0.5) VOC12 (mAP@IoU=0.5) COCO (mAP@IoU=0.5:0.95) Published In
R-CNN 58.5 - - CVPR'14
SPP-Net 59.2 - - ECCV'14
MR-CNN 78.2 (07+12) 73.9 (07+12) - ICCV'15
Fast R-CNN 70.0 (07+12) 68.4 (07++12) 19.7 ICCV'15
Faster R-CNN 73.2 (07+12) 70.4 (07++12) 21.9 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) 31.2 ECCV'16
GBDNet 77.2 (07+12) - 27.0 ECCV'16
CPF 76.4 (07+12) 72.6 (07++12) - ECCV'16
R-FCN 79.5 (07+12) 77.6 (07++12) 29.9 NIPS'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) 33.2 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) 27.4 CVPR'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
DSOD 77.7 (07+12) 76.3 (07++12) - ICCV'17
SMN 70.0 - - ICCV'17
Light-Head R-CNN - - 41.5 arXiv'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
SNIP - - 45.7 CVPR'18
Relation-Network - - 32.5 CVPR'18
Cascade R-CNN - - 42.8 CVPR'18
MLKP 80.6 (07+12) 77.2 (07++12) 28.6 CVPR'18
Fitness-NMS - - 41.8 CVPR'18
RFBNet 82.2 (07+12) - - ECCV'18
CornerNet - - 42.1 ECCV'18
PFPNet 84.1 (07+12) 83.7 (07++12) 39.4 ECCV'18
Pelee 70.9 (07+12) - - NIPS'18
HKRM 78.8 (07+12) - 37.8 NIPS'18
M2Det - - 44.2 AAAI'19
R-DAD 81.2 (07++12) 82.0 (07++12) 43.1 AAAI'19
ScratchDet 84.1 (07++12) 83.6 (07++12) 39.1 CVPR'19
Libra R-CNN - - 43.0 CVPR'19
Reasoning-RCNN 82.5 (07++12) - 43.2 CVPR'19
FSAF - - 44.6 CVPR'19
AmoebaNet + NAS-FPN - - 47.0 CVPR'19
Cascade-RetinaNet - - 41.1 CVPR'19
HTC - - 47.2 CVPR'19
TridentNet - - 48.4 ICCV'19
DAFS 85.3 (07+12) 83.1 (07++12) 40.5 ICCV'19
Auto-FPN 81.8 (07++12) - 40.5 ICCV'19
FCOS - - 44.7 ICCV'19
FreeAnchor - - 44.8 NeurIPS'19
DetNAS 81.5 (07++12) - 42.0 NeurIPS'19
NATS - - 42.0 NeurIPS'19
AmoebaNet + NAS-FPN + AA - - 50.7 arXiv'19
SpineNet - - 52.1 arXiv'19
CBNet - - 53.3 AAAI'20
EfficientDet - - 52.6 CVPR'20
DetectoRS - - 54.7 arXiv'20

2014

2015

2016

2017

2018

2019