One-Stage Object Detection Models

One-Stage Object Detection Models refer to a class of object detection models which are one-stage, i.e. models which skip the region proposal stage of two-stage models and run detection directly over a dense sampling of locations. These types of model usually have faster inference (possibly at the cost of performance). Below you can find a continuously updating list of one-stage object detection models.

METHOD YEAR PAPERS
SSD
2015 141
RetinaNet
2017 95
YOLOv3
2018 74
YOLOv2
2016 37
FCOS
2019 21
CenterNet
2019 15
YOLOv4
2020 13
EfficientDet
2019 6
CornerNet
2018 5
YOLOv1
2015 3
ExtremeNet
2019 2
FoveaBox
2019 2
M2Det
2018 1
RFB Net
2017 1
CornerNet-Squeeze
2019 1
CornerNet-Saccade
2019 1
RetinaMask
2019 1