FrameWise CNNBased View Synthesis for Light Field Camera Arrays The paper proposes a novel framewise view synthesis method based on convolutional neural networks (CNNs) for widebaseline light field (LF) camera arrays. A novel neural network architecture that follows a multiresolution processing paradigm is employed to synthesize an entire view. A novel loss function formulation based on the structural similarity index (SSIM) is proposed. A widebaseline LF image dataset is generated and employed to train the proposed deep model. The proposed method synthesizes each subaperture image (SAI) from a LF image based on corresponding SAIs from two reference LF images. Experimental results show that the proposed method yields promising results with an average PSNR and SSIM of 34.71 dB and 0.9673 respectively for wide baselines.

DepthGuided View Synthesis for Light Field Reconstruction From a Single Image Abstract   Light field imaging has recently become a promising technology for 3D rendering and displaying. However, capturing realworld light field images still faces many challenges in both the quantity and quality. In this paper, we develop a learning based technique to reconstruct light field from a single 2D RGB image. It includes three steps: unsupervised monocular depth estimation, view synthesis and depthguided view inpainting. We first propose a novel monocular depth estimation network to predict disparity maps of each subaperture views from the central view of light field. Then we synthesize the initial subaperture views by using the warping scheme. Considering that occlusion makes synthesis ambiguous for pixels invisible in the central view, we present a simple but effective fully convolutional network (FCN) for view inpainting. Note that the proposed network architecture is a general framework for light field reconstruction, which can be extended to take a sparse set of views as input without changing any structure or parameters of the network. Comparison experiments demonstrate that our method outperforms the stateoftheart light field reconstruction methods with singleview input, and achieves comparable results with the multiinput methods.