METHOD FOR TRAINING A CONVOLUTIONAL RECURRENT NEURAL NETWORK AND FOR SEMANTIC SEGMENTATION OF INPUTTED VIDEO USING THE TRAINED CONVOLUTIONAL RECURRENT NEURAL NETWORK

摘要

A method of training a convolutional recurrent neural network for semantic segmentation of videos includes: (a) training a first convolutional neural network using a set of semantically segmented training images; And (b) training a convolutional recurrent neural network, corresponding to the first convolutional neural network, using a set of semantically segmented training videos.- The convolutional layer has a hidden state. Replaced by module-includes. Training the convolutional recurrent neural network includes consecutive frames of one video of the set of semantically segmented training videos ( For each pair of ), the internal state of the cyclic layer is adapted according to the estimated optical flow between the frames of the pair of consecutive frames, so that the internal state adapts to the motion of the pixels between the pair of frames ( adapt), warping and learning at least the parameters of the cyclic module.