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Models/AWADA

AWADA

Reported on 6 benchmarks across 2 tasks · 1 paper · 4 SOTA

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

Methodology3 results

Domain AdaptationonBDD100k to Cityscapes
mAP· 2022-08-31
31.5
best: 46.5 (RT-DATR(real-time, 640x640，R-34))
SOTA
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662
Domain AdaptationonSIM10K to Cityscapes
mAP@0.5· 2022-08-31
54.1
best: 77.8 (ALDI++)
SOTA
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662
Domain AdaptationonCityscapes to Foggy Cityscapes
mAP@0.5· 2022-08-31
44.8
best: 66.8 (ALDI++(Resnet50+FPN))
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662

Other3 results

Unsupervised Domain AdaptationonBDD100k to Cityscapes
mAP· 2022-08-31
31.5
best: 46.5 (RT-DATR(real-time, 640x640，R-34))
SOTA
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662
Unsupervised Domain AdaptationonSIM10K to Cityscapes
mAP@0.5· 2022-08-31
54.1
best: 77.8 (ALDI++)
SOTA
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662
Unsupervised Domain AdaptationonCityscapes to Foggy Cityscapes
mAP@0.5· 2022-08-31
44.8
best: 66.8 (ALDI++(Resnet50+FPN))
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection arXiv:2208.14662