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Models/FPN

FPN

Reported on 22 benchmarks across 10 tasks · 2 papers · 18 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

Facial Landmark Detectionon300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517
Face Reconstructionon300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517
3D Face Reconstructionon300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517
Pedestrian DetectiononTJU-Ped-traffic
ALL (miss rate)· 2016-12-09
37.78
best: 41.4 (RetinaNet)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Pedestrian DetectiononTJU-Ped-traffic
HO (miss rate)· 2016-12-09
60.3
best: 63.73 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Pedestrian DetectiononTJU-Ped-traffic
R (miss rate)· 2016-12-09
22.3
best: 24.35 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Pedestrian DetectiononTJU-Ped-traffic
R+HO (miss rate)· 2016-12-09
26.71
best: 28.86 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Pedestrian DetectiononTJU-Ped-traffic
RS (miss rate)· 2016-12-09
35.19
best: 37.92 (RetinaNet)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144

Robots5 results

Autonomous VehiclesonTJU-Ped-traffic
ALL (miss rate)· 2016-12-09
37.78
best: 41.4 (RetinaNet)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Autonomous VehiclesonTJU-Ped-traffic
HO (miss rate)· 2016-12-09
60.3
best: 63.73 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Autonomous VehiclesonTJU-Ped-traffic
R (miss rate)· 2016-12-09
22.3
best: 24.35 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Autonomous VehiclesonTJU-Ped-traffic
R+HO (miss rate)· 2016-12-09
26.71
best: 28.86 (FCOS)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Autonomous VehiclesonTJU-Ped-traffic
RS (miss rate)· 2016-12-09
35.19
best: 37.92 (RetinaNet)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144

Medical4 results

3D Face Modellingon300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517
Semantic Segmentationon Potsdam
mIoU· 2016-12-09
82.99
best: 86.39 (LMFNet-3)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Semantic Segmentationon US3D
mIoU· 2016-12-09
72.51
best: 85.09 (LMFNet-3)
Feature Pyramid Networks for Object Detection arXiv:1612.03144
Semantic SegmentationonVaihingen
mIoU· 2016-12-09
74.86
best: 82.87 (CMX)
Feature Pyramid Networks for Object Detection arXiv:1612.03144

Audio3 results

10-shot image generationon Potsdam
mIoU· 2016-12-09
82.99
best: 86.39 (LMFNet-3)
SOTA
Feature Pyramid Networks for Object Detection arXiv:1612.03144
10-shot image generationon US3D
mIoU· 2016-12-09
72.51
best: 85.09 (LMFNet-3)
Feature Pyramid Networks for Object Detection arXiv:1612.03144
10-shot image generationonVaihingen
mIoU· 2016-12-09
74.86
best: 82.87 (CMX)
Feature Pyramid Networks for Object Detection arXiv:1612.03144

Music1 result

Facial Recognition and Modellingon300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517

Methodology1 result

3Don300W
Mean Error Rate· 2017-08-24
0.1043
SOTA
FacePoseNet: Making a Case for Landmark-Free Face Alignment arXiv:1708.07517