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Models/OVR-CNN

OVR-CNN

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

3DonMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
2D ClassificationonMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
2D Object DetectiononMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
16konMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678

Computer Vision2 results

Object DetectiononMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678
Open Vocabulary Object DetectiononMSCOCO
AP 0.5· 2020-11-20
22.8
best: 50.3 (Cooperative Foundational Models)
SOTA
Open-Vocabulary Object Detection Using Captions arXiv:2011.10678