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Reported on 5 benchmarks across 5 tasks · 1 paper

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

Computer Vision4 results

VideoonTHUMOS 2014
mAP@0.5· 2017-04-13
6.8
best: 52.2 (HR-Pro)
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization arXiv:1704.04232
Temporal Action LocalizationonTHUMOS 2014
mAP@0.5· 2017-04-13
6.8
best: 52.2 (HR-Pro)
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization arXiv:1704.04232
Action LocalizationonTHUMOS 2014
mAP@0.5· 2017-04-13
6.8
best: 52.2 (HR-Pro)
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization arXiv:1704.04232
Weakly Supervised Action LocalizationonTHUMOS 2014
mAP@0.5· 2017-04-13
6.8
best: 52.2 (HR-Pro)
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization arXiv:1704.04232

Methodology1 result

Zero-Shot LearningonTHUMOS 2014
mAP@0.5· 2017-04-13
6.8
best: 52.2 (HR-Pro)
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization arXiv:1704.04232