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Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
In this paper, a novel convolutional neural network (CNN)-based framework is developed for light field reconstruction from a sparse set of views. We indicate that the reconstruction can be efficiently modeled as angular restoration on an epipolar plane image (EPI). The main problem in direct reconstruction on the EPI involves an information asymmetry between the spatial and angular dimensions, where the detailed portion in the angular dimensions is damaged by undersampling. Directly upsamplingdoi:10.1109/tpami.2018.2845393 pmid:29994195 fatcat:xzuaadt2orb5lgopxs2ht3ejsm