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Deep Neural Networks Achieve Best Classification Accuracy On Videos. However, Traditional Methods Or Shallow Architectures Remain Competitive And Combinations Of Different Network Types Are The Usual Chosen Approach. A Reason For This Less Important Impact Of Deep Methods For Video Recognition Is The Motion Representation. The Time Has A Stronger Redundancy, And An Important Elasticity Compared To The Spatial Dimensions. The Temporal Redundancy Is Evident, But The Elasticity Within An Action Class Is Well Less Considered .Several Instances Of The Action Still Widely Differ By Their Style And Speed Of Execution.