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Models/OVR (ResNet50)

OVR (ResNet50)

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

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

Methodology4 results

3DonOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
2D ClassificationonOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
2D Object DetectiononOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
16konOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678

Computer Vision2 results

Object DetectiononOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
Open Vocabulary Object DetectiononOVAD benchmark
mean average precision· 2020-11-20
15.1
best: 27.2 (OvarNet (ViT-B16))
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678