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Perceptual Loss for Convolutional Neural Network Based Optical Flow Estimation
2017
DEStech Transactions on Computer Science and Engineering
Convolutional Neural Networks (CNNs) are successfully used in optical flow estimation as learned patch based descriptors. In this work, rather training feature descriptors via CNNs, an end-to-end fully convolutional network, is developed for solving optical flow from a pair of images. Motivated by the success in image transformation tasks, a perceptual loss function is used for training the network for optical flow estimation. We trained a deep convolutional auto-encoder of optical flow field
doi:10.12783/dtcse/smce2017/12437
fatcat:6oeq4zzshffjbfrhimeuytf36q