Browsing by Author "Lee, Sungkil"

Now showing 1 - 3 of 3
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    Day-to-Night Road Scene Image Translation Using Semantic Segmentation
    (The Eurographics Association, 2020) Baek, Seung Youp; Lee, Sungkil; Lee, Sung-hee and Zollmann, Stefanie and Okabe, Makoto and Wuensche, Burkhard
    We present a semi-automated framework that translates day-time domain road scene images to those for the night-time domain. Unlike recent studies based on the Generative Adversarial Networks (GANs), we avoid learning for the translation without random failures. Our framework uses semantic annotation to extract scene elements, perceives a scene structure/depth, and applies per-element translation. Experimental results demonstrate that our framework can synthesize higher-resolution results without artifacts in the translation.
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    Hierarchical Raster Occlusion Culling
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Lee, Gi Beom; Jeong, Moonsoo; Seok, Yechan; Lee, Sungkil; Mitra, Niloy and Viola, Ivan
    This paper presents a scalable online occlusion culling algorithm, which significantly improves the previous raster occlusion culling using object-level bounding volume hierarchy. Given occluders found with temporal coherence, we find and rasterize coarse groups of potential occludees in the hierarchy. Within the rasterized bounds, per-pixel ray casting tests fine-grained visibilities of every individual occludees. We further propose acceleration techniques including the read-back of counters for tightly-packed multidrawing and occluder filtering. Our solution requires only constant draw calls for batch occlusion tests, while avoiding costly iteration for hierarchy traversal. Our experiments prove our solution outperforms the existing solutions in terms of scalability, culling efficiency, and occlusion-query performance.
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    MegaViews: Scalable Many‐View Rendering With Concurrent Scene‐View Hierarchy Traversal
    (© 2019 The Eurographics Association and John Wiley & Sons Ltd., 2019) Kol, Timothy R.; Bauszat, Pablo; Lee, Sungkil; Eisemann, Elmar; Chen, Min and Benes, Bedrich
    We present a scalable solution to render complex scenes from a large amount of viewpoints. While previous approaches rely either on a scene or a view hierarchy to process multiple elements together, we make full use of both, enabling sublinear performance in terms of views and scene complexity. By concurrently traversing the hierarchies, we efficiently find shared information among views to amortize rendering costs. One example application is many‐light global illumination. Our solution accelerates shadow map generation for virtual point lights, whose number can now be raised to over a million while maintaining interactive rates.