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Models/Beta R-CNN

Beta R-CNN

Reported on 18 benchmarks across 7 tasks · 1 paper

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

Methodology8 results

3DonCrowdHuman (full body)
AP· 2022-10-23
89.6
best: 97.2 (InternImage-H)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
3DonCrowdHuman (full body)
mMR· 2022-10-23
40.3
best: 50.49 (Faster RCNN (ResNet50))
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
2D ClassificationonCrowdHuman (full body)
AP· 2022-10-23
89.6
best: 97.2 (InternImage-H)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
2D ClassificationonCrowdHuman (full body)
mMR· 2022-10-23
40.3
best: 50.49 (Faster RCNN (ResNet50))
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
2D Object DetectiononCrowdHuman (full body)
AP· 2022-10-23
89.6
best: 97.2 (InternImage-H)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
2D Object DetectiononCrowdHuman (full body)
mMR· 2022-10-23
40.3
best: 50.49 (Faster RCNN (ResNet50))
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
16konCrowdHuman (full body)
AP· 2022-10-23
89.6
best: 97.2 (InternImage-H)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
16konCrowdHuman (full body)
mMR· 2022-10-23
40.3
best: 50.49 (Faster RCNN (ResNet50))
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758

Computer Vision6 results

Object DetectiononCrowdHuman (full body)
AP· 2022-10-23
89.6
best: 97.2 (InternImage-H)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Object DetectiononCrowdHuman (full body)
mMR· 2022-10-23
40.3
best: 50.49 (Faster RCNN (ResNet50))
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Pedestrian DetectiononCityPersons
Bare MR^-2· 2022-10-23
6.4
best: 10 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Pedestrian DetectiononCityPersons
Heavy MR^-2· 2022-10-23
47.1
best: 56.9 (RepLoss)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Pedestrian DetectiononCityPersons
Partial MR^-2· 2022-10-23
10.3
best: 17.2 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Pedestrian DetectiononCityPersons
Reasonable MR^-2· 2022-10-23
10.6
best: 15.5 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758

Robots4 results

Autonomous VehiclesonCityPersons
Bare MR^-2· 2022-10-23
6.4
best: 10 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Autonomous VehiclesonCityPersons
Heavy MR^-2· 2022-10-23
47.1
best: 56.9 (RepLoss)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Autonomous VehiclesonCityPersons
Partial MR^-2· 2022-10-23
10.3
best: 17.2 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758
Autonomous VehiclesonCityPersons
Reasonable MR^-2· 2022-10-23
10.6
best: 15.5 (TLL)
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective arXiv:2210.12758