一、目标检测方法

Anchor

1. One Stage

Yolo Family：yolov1...yolov3...yolov5
SSD Family
RetinaNet
M2Det

2. Two Stage

RCNN
Fast RCNN
Faster RCNN
Mask RCNN
RFCN
Light-Head-RCNN
Cascade RCNN
Libra RCNN
DetectoRS

Anchor Free

ConnerNet
Foveabox
CenterNet
FCOS
RepPoint
ATSS
FreeAnchor
FSAF

Transformer

DETR

NAS

DetNAS
NAS-FPN
Auto-FPN
NAS-FCOS
SpineNet
Hit-Detector
EfficientDet

Semi-supervised learning

STAC

二、Tricks

Data Augmentation

SSD augmentation
Random erase
Mixup
Mosaic

Anchor

Guided Anchor

NMS

Soft-NMS

Loss

1. Classification 分类

Focal loss 焦点损失
Generalized Focal loss 广义焦点损失

2. Regression 回归

IoU
GIoU
DIoU
CIoU

Imbalance

Class
Scale
Spatial
Objective

参考文章

版权声明：本文为CSDN博主「沉醉，于风中」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/weixin_51697369/article/details/121136053