2D-ObjectDetection算法综述

本文主要是介绍2D-ObjectDetection算法综述，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

layout: post
title: 2D检测算法综述(2D Detection)
date: 2021-07-25 17:19:40.000000000 +09:00
categories: [算法篇]
tags: [CV, 综述]

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前言
公开数据集
经典论文
基本结构
Backbone
超参
Loss
经典检测经典框架
网络加速
通用检测Tricks
部分论文解读Links

前言

update on 4/10/2021: 终于完成了2D_Detection系列，算是对之前自己在这个领域工作的一点回顾，之后自己会不定期更新一些深度学习模型部署的文章以及论文解读的文章

~~本文旨在总结之前自己涉及的 2D-Detection 相关的知识内容，按照下文组织内容，分篇章不定时更新。~~

主要参考来源：

<<深度学习之Pytorch物体检测实战>>
网络: 知乎 / CSDN etc

公开数据集

常用的数据集链接如下：

2D物体检测数据集:
- Pascal VOC
- Object365
- COCO
3D物体检测数据集:
- KITTI
- nuScenes
- Lyft
- Waymo

经典论文

说明：更新于2021-05-02

参考：github_object_detection

不同Detectio算法框架性能对比:

| Detector | VOC07(mAP@IoU=0.5) | VOC12(mAP@IoU=0.5) | COCO(mAP@IoU=0.5:0.95) | Published In |
| RCNN | 58.5 | - | - | CVPR’14 |
| SPP-Net | 59.2 | - | - | ECCV’14 |
| MR-CNN | 78.2(07+12) | 73.9(07+12) | - | ICCV’15 |
| Fast RCNN | 70.0(07+12) | 68.4(07+12) | 19.7 | ICCV’15 |
| Faster RCNN | 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 | |
| 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 |
| E-DAD | 81.2 | 82.0 | 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 |
| TridenNet | - | - | 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 |
| EfficientDet | - | - | 51.0 | arXiv’19 |