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Synthesizing a densely sampled light field from a single image is highly beneficial for many applications. Moreover, jointly solving both angular and spatial super-resolution problem also introduces new possibilities in light field imaging. The conventional method relies on physical-based rendering and a secondary network to solve the angular super-resolution problem. In addition, pixel-based loss limits the network capability to infer scene geometry globally. In this paper, we show that bothdoi:10.1109/access.2020.3002921 fatcat:xcxl6lp2hzfsljqeiufzmje3wi