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YH Technologies at ActivityNet Challenge 2018
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This notebook paper presents an overview and comparative analysis of our systems designed for the following five tasks in ActivityNet Challenge 2018: temporal action proposals, temporal action localization, dense-captioning events in videos, trimmed action recognition, and spatio-temporal action localization.
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Three Branches: Detecting Actions With Richer Features
A three-branch fusion of SlowFast global features, person-level RoI features, and long-term feature banks reaches 32.49% mAP on AVA and 21.59% error on Kinetics-700.
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