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Paper Detail

Paper IDTEC-5.1
Paper Title ROBUST LIGHT FIELD SYNTHESIS FROM STEREO IMAGES WITH LEFT-RIGHT GEOMETRIC CONSISTENCY
Authors Chun-Hao Chao, Chang-Le Liu, Homer H. Chen, National Taiwan University, Taiwan
SessionTEC-5: Image and Video Processing 1
LocationArea G
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Image and Video Processing: Formation and reconstruction
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract We propose a lightweight yet effective deep learning pipeline for light field synthesis from a single stereo image pair. Our pipeline consists of a convolutional network (CNN) that enforces a left-right consistency constraint on the light fields synthesized from left and right stereo views, a stage that merges light fields synthesized from left and right stereo views with a novel alpha blending technique, and a final refinement network using a unique 3D convolution operation. Our experiments quantitatively and qualitatively confirm the effectiveness and robustness of the proposed model, which performs favorably against state-of-the-art algorithms for light field synthesis from extremely sparse (only one, two, or four) views while using much fewer parameters.