Methods > Computer Vision

Object Detection Models

Object Detection Models are architectures used to perform the task of object detection. Below you can find a continuously updating list of object detection models.

METHOD YEAR PAPERS
Faster R-CNN
2015 280
Mask R-CNN
2017 222
SSD
2015 153
RetinaNet
2017 112
YOLOv3
2018 93
YOLOv2
2016 40
R-FCN
2016 32
R-CNN
2013 29
FCOS
2019 26
Fast R-CNN
2015 26
YOLOv4
2020 21
Cascade R-CNN
2017 19
CenterNet
2019 16
Detr
2020 13
EfficientDet
2019 8
HTC
2019 7
CornerNet
2018 6
GCNet
2019 5
PANet
2018 5
RepPoints
2019 4
YOLOv1
2015 3
ThunderNet
2019 3
Grid R-CNN
2018 3
ExtremeNet
2019 2
Libra R-CNN
2019 2
FoveaBox
2019 2
NAS-FCOS
2019 2
VFNet
2020 2
TridentNet
2019 1
M2Det
2018 1
RPDet
2019 1
CornerNet-Squeeze
2019 1
RFB Net
2017 1
CornerNet-Saccade
2019 1
RetinaMask
2019 1
Dynamic R-CNN
2020 1
H3DNet
2000 1
SASA
2019 1
MutualGuide
2020 1
CentripetalNet
2020 1
SABL
2019 1
Sparse R-CNN
2020 1
HRI pipeline
2000 0