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Sungkil Lee, Younguk Kim, and Elmar Eisemann

ACM Trans. Graphics, 37(5), 177:1–13, 2018.
Presented at ACM SIGGRAPH 2019
This article presents an iterative backward-warping technique and its applications. It predictively synthesizes depth buffers for novel views. Our solution is based on a fixed-point iteration that converges quickly in practice. Unlike the previous techniques, our solution is a pure backward warping without using bidirectional sources. To efficiently seed the iterative process, we also propose a tight bounding method for motion vectors. Non-convergent depth holes are inpainted via deep depth buffers. Our solution works well with arbitrarily distributed motion vectors under moderate motions. Many scenarios can benefit from our depth warping. As an application, we propose a highly scalable image-based occlusion-culling technique, achieving a significant speedup compared to the state of the art. We also demonstrate the benefit of our solution in multi-view soft-shadow generation.
Paper preprints, slides, supplementary materials, and Google Scholar entry
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@ARTICLE{lee18:dw, title={{Iterative Depth Warping}}, author={Sungkil Lee and Younguk Kim and Elmar Eisemann}, journal={{ACM Trans. Graphics}}, volume={37}, number={5}, pages={177:1--13}, year={2018} }

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