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    Thin Structures in Image Based Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Thonat, Theo; Djelouah, Abdelaziz; Durand, Fredo; Drettakis, George; Jakob, Wenzel and Hachisuka, Toshiya
    We propose a novel method to handle thin structures in Image-Based Rendering (IBR), and specifically structures supported by simple geometric shapes such as planes, cylinders, etc. These structures, e.g. railings, fences, oven grills etc, are present in many man-made environments and are extremely challenging for multi-view 3D reconstruction, representing a major limitation of existing IBR methods. Our key insight is to exploit multi-view information. After a handful of user clicks to specify the supporting geometry, we compute multi-view and multi-layer alpha mattes to extract the thin structures. We use two multi-view terms in a graph-cut segmentation, the first based on multi-view foreground color prediction and the second ensuring multiview consistency of labels. Occlusion of the background can challenge reprojection error calculation and we use multiview median images and variance, with multiple layers of thin structures. Our end-to-end solution uses the multi-layer segmentation to create per-view mattes and the median colors and variance to create a clean background. We introduce a new multi-pass IBR algorithm based on depth-peeling to allow free-viewpoint navigation of multi-layer semi-transparent thin structures. Our results show significant improvement in rendering quality for thin structures compared to previous image-based rendering solutions.
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    Exploiting Repetitions for Image-Based Rendering of Facades
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Rodriguez, Simon; Bousseau, Adrien; Durand, Fredo; Drettakis, George; Jakob, Wenzel and Hachisuka, Toshiya
    Street-level imagery is now abundant but does not have sufficient capture density to be usable for Image-Based Rendering (IBR) of facades. We present a method that exploits repetitive elements in facades - such as windows - to perform data augmentation, in turn improving camera calibration, reconstructed geometry and overall rendering quality for IBR. The main intuition behind our approach is that a few views of several instances of an element provide similar information to many views of a single instance of that element. We first select similar instances of an element from 3-4 views of a facade and transform them into a common coordinate system, creating a ''platonic'' element. We use this common space to refine the camera calibration of each view of each instance and to reconstruct a 3D mesh of the element with multi-view stereo, that we regularize to obtain a piecewise-planar mesh aligned with dominant image contours. Observing the same element under multiple views also allows us to identify reflective areas - such as glass panels - which we use at rendering time to generate plausible reflections using an environment map. Our detailed 3D mesh, augmented set of views, and reflection mask enable image-based rendering of much higher quality than results obtained using the input images directly.