C3D and Localization Model for Locating and Recognizing the Actions from Untrimmed Videos (Student Abstract)
Keywords:Video Analysis, Action Recognition, Action Localization
AbstractIn this article, we proposed a technique for action localization and recognition from long untrimmed videos. It consists of C3D CNN model followed by the action mining using the localization model, where the KNN classifier is used. We segment the video into expressible sub-action known as action-bytes. The pseudo labels have been used to train the localization model, which makes the trimmed videos untrimmed for action-bytes. We present experimental results on the recent benchmark trimmed video dataset “Thumos14”.
How to Cite
Singh, H., Pallewad, T., Subudhi, B. N., & Jakhetiya, V. (2022). C3D and Localization Model for Locating and Recognizing the Actions from Untrimmed Videos (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13051-13052. https://doi.org/10.1609/aaai.v36i11.21662
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