randomly subsampling a sequence of video frames captured from one or more video cameras;

randomly reversing the subsampled sequence of video frames to define a plurality of sub-sequences of randomly reversed video frames;

training, in a training mode, a video reasoning model with temporally augmented input, including the plurality of sub-sequences of randomly reversed video frames, to make predictions over temporally augmented target classes;

updating parameters of the video reasoning model by a machine learning algorithm by discarding a final prediction to retain the temporally augmented target classes with corresponding original classes; and

deploying, in an inference mode, the video reasoning model, with overfitting suppression through a learned temporal order of video frames to determine the original classes, in the video reasoning system to make the final prediction related to classify a human action in the sequence of video frames.