mAP@0.1:0.7: 47.3mAP@0.5: 37.3
Papers with Code · CC BY-SA 4.0
Weakly Supervised Action Localization
In this task, the training data consists of videos with a list of activities in them without any temporal boundary annotations. However, while testing, given a video, the algorithm should recognize the activities in the video and also provide the start and end time.
논문
mAP@0.1:0.7: 43.5mAP@0.5: 33.9
mAP@0.1:0.7: 33.7mAP@0.5: 21.9
mAP@0.1:0.7: 31.0mAP@0.5: 19.3
mAP@0.1:0.7: 49.2
mAP@0.1:0.7: 36.4mAP@0.5: 28.8
mAP@0.5: 34.6mAP@0.1:0.7: 42.6mAP@0.1:0.5: 53.2
mAP@0.5: 36.9mAP@0.1:0.7: 46.4mAP@0.1:0.5: 56.9
mAP@0.5: 30.1mAP@0.1:0.7: 37.8mAP@0.1:0.5: 46.9
mAP@0.5: 27mAP@0.1:0.7: 35.3mAP@0.1:0.5: 43.6
mAP@0.5: 32.2mAP@0.1:0.7: 40.9mAP@0.1:0.5: 50.3
mAP@0.5: 38.3mAP@0.1:0.7: 44.6mAP@0.1:0.5: 54.4
mAP@0.1:0.7: 76.9mAP@0.5: 66.3
mAP@0.5: 41.8mAP@0.1:0.7: 50.6mAP@0.1:0.5: 61.5
mAP@0.5: 42.8mAP@0.1:0.7: 49.6mAP@0.1:0.5: 60.1
mAP@0.5: 40.0mAP@0.1:0.7: 47.0mAP@0.1:0.5: 57.4
mAP@0.5: 37.1mAP@0.1:0.7: 46.2mAP@0.1:0.5: 57.2
mAP@0.5: 41.0mAP@0.1:0.7: 48.5mAP@0.1:0.5: 59.1
mAP@0.5: 28.8mAP@0.1:0.7: 37.0mAP@0.1:0.5: 45.6
mAP@0.5: 33.7mAP@0.1:0.7: 41.9mAP@0.1:0.5: 51.6