梳理一遍，还需补充哪些欢迎指出。 指标 MS COCO
一、单阶段目标检测（基于anchor的）
| multi-scale | backbone | arxiv/ github | AP | AP50 | AP75 | APs | APM | APL | 亮点 | time | |
| YOLO | DarkNet-53 | ||||||||||
| SSD300（Google） |
VGG | https://arxiv.org/pdf/1512.02325.pdf | 23.2 | 41.2 | 23.4 | 5.3 | 23.2 | 38.6 | |||
| SSD512x512 | VGG | 26.8 | 46.5 | 27.8 | 9.0 | 28.9 | 41.9 | ||||
| RetinaNet （FAIR facebook） |
ResNet101FPN | https://arxiv.org/pdf/1708.02002.pdf | 39.1 | 59.1 | 42.3 | 21.8 | 42.7 | 50.2 | Focal loss 类别平衡损失 | ||
| ResNeXt101 | 40.8 | 61.1 | 44.1 | 24.1 | 44.2 | 51.2 | |||||
| RefineDet512 （ 中科院） |
ResNet101 | https://arxiv.org/pdf/1711.06897.pdf | 36.4 | 57.5 | 39.5 | 16.6 | 39.9 | 51.4 | |||
| √ | 41.8 | 62.9 | 45.7 | 25.6 | 45.1 | 54.1 | |||||
| M2Det （阿里达摩+北大） |
VGG16 | https://arxiv.org/pdf/1811.04533.pdf | 41.0 | 59.7 | 45.0 | 22.1 | 46.5 | 53.8 | |||
| 512x512 | √ | VGG16 | 44.2 | 64.6 | 49.3 | 29.2 | 47.9 | 55.1 | |||
| 800x800 | ResNet101 | 38.8 | 59.4 | 41.7 | 20.5 | 43.9 | 53.4 | ||||
| √ | ResNet101 | 43.9 | 64.4 | 48.4 | 29.6 | 49.6 | 54.3 | ||||
| YOLO-v4 512X512 | CSPDarknet-53 | https://arxiv.org/pdf/2004.10934.pdf | 43.0 | 64.9 | 46.5 | 24.3 | 46.1 | 55.2 | |||
| 608 | CSPDarknet-53 | 43.5 | 65.7 | 47.3 | 26.7 | 46.7 | 53.3 |
二、Anchor-Free
| multi-scale | arxiv | backbone | AP | AP50 | AP75 | APS | APM | APL | 亮点 | |
| CornetNet | https://arxiv.org/pdf/1808.01244.pdf | Hourglass 104 | 40.5 | 56.5 | 43.1 | 19.4 | 42.7 | 53.9 | ||
| √ | Hourglass 104 | 42.1 | 57.8 | 45.3 | 20.8 | 44.8 | 56.7 | |||
| ExtremNet | https://arxiv.org/pdf/1901.08043.pdf | Hourglass 104 | 40.2 | 55.5 | 43.2 | 20.4 | 43.2 | 53.1 | ||
| √ | Hourglass 104 | 43.7 | 60.5 | 47.0 | 24.1 | 46.9 | 57.6 | |||
| FSAF800 | https://arxiv.org/pdf/1903.00621.pdf | ResNext-101 | 42.9 | 63.8 | 46.3 | 26.6 | 46.2 | 52.7 | ||
| FSAF | √ | 44.6 | 65.2 | 48.6 | 29.7 | 47.1 | 54.6 | |||
| FCOS | https://arxiv.org/pdf/1904.01355.pdf | Hourglass109 | 40.5 | 56.5 | 43.1 | 19.4 | 42.7 | 53.9 | ||
| ResNeXt-64x4d-101-FPN | 44.7 | 64.1 | 48.1 | 27.6 | 47.5 | 55.6 | ||||
| FoveaBox | https://arxiv.org/pdf/1904.03797v1.pdf | resnet101 | 40.6 | 60.1 | 43.5 | 23.3 | 45.2 | 54.5 | ||
| ResNeXt101 | 42.1 | 61.9 | 45.2 | 24.9 | 46.8 | 55.6 | ||||
| RPDet | https://arxiv.org/pdf/1904.11490.pdf | ResNet101 | 41.0 | 62.9 | 44.3 | 23.6 | 44.1 | 51.7 | ||
| √ | ResNet101-DCN | 43.5 | 61.3 | 46.7 | 25.3 | 45.3 | 55.0 | |||
| CenterNet：keypoint triplet | https://arxiv.org/pdf/1904.08189.pdf | Hourglass 52 | 41.6 | 59.4 | 44.2 | 22.5 | 43.1 | 54.1 | ||
| Hourglass 104 | 44.9 | 62.9 | 48.1 | 25.6 | 47.4 | 57.4 | ||||
| √ | Hourglass 52 | 43.5 | 61.3 | 46.7 | 25.3 | 45.3 | 55.0 | |||
| √ | Hourglass 104 | 47.0 | 64.5 | 50.7 | 28.9 | 49.9 | 58.9 |
三、二阶段目标检测：
Faster RCNN
DetNet 2018
Cascade RCNN
LibraRCNN
efficientDet
maskrcnn
四、轻量化的目标检测
| input size | backbone | arxiv | AP | AP50 | AP75 | 亮点 | ||
| ThunderNet | 320x320 | SNet146 | https://arxiv.org/pdf/1903.11752.pdf | 23.6 | 40.2 | 24.5 | ||
| 320x320 | SENet535 | 28.0 | 46.2 | 29.5 | ||||