DOTA-DOAI
Abstract
This repo is the codebase for our team to participate in DOTA related competitions, including rotation and horizontal detection. We mainly use FPN -based two-stage detector, and it is completed by YangXue and YangJirui .
Performance
DOTA1.0 (Task1)
Model
Backbone
Training data
Val data
mAP
Model Link
Tricks
lr schd
Data Augmentation
GPU
Image/GPU
Configs
FPN (baseline)
ResNet50_v1 (600,800,1024)->800
DOTA1.0 trainval
DOTA1.0 test
69.35
model
No
1x
No
2X GeForce RTX 2080 Ti
1
cfgs_dota1.0_res50_v2.py
FPN
ResNet50_v1d (600,800,1024)->800
DOTA1.0 trainval
DOTA1.0 test
70.87
model
+InLD
1x
No
2X GeForce RTX 2080 Ti
1
cfgs_dota1.0_res50_v3.py
FPN
ResNet152_v1d (600,800,1024)->MS
DOTA1.0 trainval
DOTA1.0 test
76.20 (76.54)
model
ALL
2x
Yes
2X GeForce RTX 2080 Ti
1
cfgs_dota1.0_res152_v1.py
DOTA1.0 (Task2)
Model
Backbone
Training data
Val data
mAP
Model Link
Tricks
lr schd
Data Augmentation
GPU
Image/GPU
Configs
FPN (baseline)
ResNet50_v1 (600,800,1024)->800
DOTA1.0 trainval
DOTA1.0 test
76.03
model
No
1x
No
2X Quadro RTX 8000
1
cfgs_dota1.0_res50_v2.py
FPN (memory consumption)
ResNet152_v1d (600,800,1024)->MS
DOTA1.0 trainval
DOTA1.0 test
81.23
model
ALL
2x
Yes
2X Quadro RTX 8000
1
cfgs_dota1.0_res152_v1.py
Visualization
Performance of published papers on DOTA datasets
DOTA1.0 (Task1)
Model
Backbone
mAP
Paper Link
Code Link
Remark
Recommend
FR-O (DOTA)
ResNet101
52.93
CVPR2018
MXNet
DOTA dataset, baseline
✅
IENet
ResNet101
57.14
arXiv:1912.00969
-
anchor free
R2 CNN
ResNet101
60.67
arXiv:1706.09579
TF
scene text, multi-task, different pooled sizes, baseline
✅
RRPN
ResNet101
61.01
TMM arXiv:1703.01086
TF
scene text, rotation proposals, baseline
✅
RetinaNet-H
ResNet101
64.73
arXiv:1908.05612
TF
single stage, baseline
✅
Axis Learning
ResNet101
65.98
Remote Sensing
-
single stage, anchor free
✅
ICN
ResNet101
68.16
ACCV2018
-
image cascade, multi-scale
✅
RADet
ResNeXt101
69.09
Remote Sensing
-
enhanced FPN, mask rcnn
RoI Transformer
ResNet101
69.56
CVPR2019
MXNet , Pytorch
roi transformer
✅
P-RSDet
ResNet101
69.82
arXiv:2001.02988
-
anchor free, polar coordinates
✅
CAD-Net
ResNet101
69.90
TGRS arXiv:1903.00857
-
attention
O2 -DNet
Hourglass104
71.04
arXiv:1912.10694
-
anchor free
✅
SCRDet
ResNet101
72.61
ICCV2019
TF:R2 CNN++ , IoU-Smooth L1
attention, angular boundary problem
✅
SARD
ResNet101
72.95
Access
-
IoU-based weighted loss
FADet
ResNet101
73.28
ICIP2019
-
attention
R3 Det
ResNet152
73.74
arXiv:1908.05612
TF
refined single stage, feature alignment
✅
RSDet
ResNet152
74.10
arXiv:1911.08299
-
quadrilateral bbox, angular boundary problem
✅
Gliding Vertex
ResNet101
75.02
TPAMI arXiv:1911.09358
Pytorch
quadrilateral bbox
✅
Mask OBB
ResNeXt-101
75.33
Remote Sensing
-
attention, multi-task
✅
FFA
ResNet101
75.7
ISPRS
-
enhanced FPN, rotation proposals
APE
ResNeXt-101(32x4)
75.75
arXiv:1906.09447
-
length independent IoU (LIIoU)
✅
CSL
ResNet152
76.17 / 70.29
arXiv:2003.05597
TF:CSL_RetinaNet
angular boundary problem
✅
OWSR
Ensemble (ResNet101 + ResNeXt101 + mdcn-ResNet101)
76.36
CVPR2019 WorkShop TGRS
-
enhanced FPN
FPN-InLD / R3 Det-InLD (R3 Det++)
ResNet101 / ResNet152
76.81 / 76.56
-
TF:R3 Det++ , FPN-InLD
DOTA1.0 (Task2)
Model
Backbone
mAP
Paper Link
Code Link
Remark
Recommend
FR-H (DOTA)
ResNet101
60.46
CVPR2018
MXNet
DOTA dataset, baseline
✅
SBL
ResNet50
64.77
arXiv:1810.08103
-
single stage
FMSSD
VGG16
72.43
TGRS
-
IoU-based weighted loss, enhanced FPN
ICN
ResNet101
72.45
ACCV2018
-
image cascade, multi-scale
✅
IoU-Adaptive R-CNN
ResNet101
72.72
Remote Sensing
-
IoU-based weighted loss, cascade
EFR
VGG16
73.49
Remote Sensing
Pytorch
enhanced FPN
SCRDet
ResNet101
75.35
ICCV2019
TF
attention, angular boundary problem
✅
FADet
ResNet101
75.38
ICIP2019
-
attention
Mask OBB
ResNeXt-101
76.98
Remote Sensing
-
attention, multi-task
✅
A2 RMNet
ResNet101
78.45
Remote Sensing
-
attention, enhanced FPN, different pooled sizes
OWSR
Ensemble (ResNet101 + ResNeXt101 + mdcn-ResNet101)
78.79
CVPR2019 WorkShop TGRS
-
enhanced FPN
DM-FPN
ResNet-Based
79.27
Remote Sensing
-
enhanced FPN
FPN-InLD
ResNet152
81.23
-
FPN-InLD-TF
DOTA1.5 (Task1)
Model
Backbone
mAP
Paper Link
Code Link
Remark
Recommend
APE
ResNeXt-101(32x4)
78.34
arXiv:1906.09447
-
length independent IoU (LIIoU)
✅
OWSR
Ensemble (ResNet101 + ResNeXt101 + mdcn-ResNet101)
76.60
CVPR2019 WorkShop
-
enhanced FPN
DOTA1.5 (Task2)
Model
Backbone
mAP
Paper Link
Code Link
Remark
Recommend
OWSR
Ensemble (ResNet101 + ResNeXt101 + mdcn-ResNet101)
79.50
CVPR2019 WorkShop
-
enhanced FPN
Related Articles
Dataset
Some remote sensing related object detection dataset statistics are in DATASET.md