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Am I Done? Predicting Action Progress in Videos
2020
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
In this paper we deal with the problem of predicting action progress in videos. We argue that this is an extremely important task since it can be valuable for a wide range of interaction applications. To this end we introduce a novel approach, named ProgressNet, capable of predicting when an action takes place in a video, where it is located within the frames, and how far it has progressed during its execution. To provide a general definition of action progress, we ground our work in the
doi:10.1145/3402447
fatcat:7bgk4bembzbc7o4ucsm4hl4fae