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Video Action Recognition using RESNET pretrained on Imagenet for UCF 101 dataset

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Action Recognition using Deep Residual Networks

The dataset can be found here http://crcv.ucf.edu/data/UCF101.php

The model requires about 15-18 hours to train on GPU

The full output is given in the output.out file.

untitled1

Sample Output -

('Fencing', 0.97058821, 34.0) ('Kayaking', 0.97222221, 36.0) ('Rowing', 0.97222221, 36.0) ('ParallelBars', 0.97297299, 37.0) ('Biking', 0.97368419, 38.0) ('CliffDiving', 0.97435898, 39.0) ('PoleVault', 0.97500002, 40.0) ('IceDancing', 0.97826087, 46.0) ('HorseRiding', 0.97959185, 49.0) ('CuttingInKitchen', 1.0, 33.0) ('Billiards', 1.0, 40.0) ('PlayingDhol', 1.0, 49.0) ('TrampolineJumping', 1.0, 32.0) ('Diving', 1.0, 45.0) ('PlayingPiano', 1.0, 28.0) ('Haircut', 1.0, 33.0) ('BasketballDunk', 1.0, 37.0) ('SumoWrestling', 1.0, 34.0) ('SoccerPenalty', 1.0, 41.0) ('HorseRace', 1.0, 35.0) ('SkyDiving', 1.0, 31.0) ('Skijet', 1.0, 28.0) ('WritingOnBoard', 1.0, 45.0) ('PlayingSitar', 1.0, 44.0) ('TableTennisShot', 1.0, 39.0)

Acknowledgement

The Resnet code has been borrowed from https://github.com/ry/tensorflow-resnet

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Video Action Recognition using RESNET pretrained on Imagenet for UCF 101 dataset

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