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Younguk Kim

dblp:230/7910 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Rendering · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering › image-based rendering
3d image warping
0.312018
Iterative Depth Warping · ACM Trans. Graph. 2018
Rendering
image-based rendering
0.312018
Iterative Depth Warping · ACM Trans. Graph. 2018
Rendering
visibility culling
0.312018
Iterative Depth Warping · ACM Trans. Graph. 2018
Rendering › shadow rendering
soft shadows
0.112018
Iterative Depth Warping · ACM Trans. Graph. 2018

Methods — techniques the papers use, named apart from their topics

inpainting · 0.3fixed-point iteration · 0.3backward warping · 0.3
YearPublicationVenuePosition
2018 Iterative Depth Warping
abstract
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 speed-up compared to the state of the art. We also demonstrate the benefit of our solution in multi-view soft-shadow generation.
Sungkil Lee 0002, Younguk Kim, Elmar Eisemann
ACM Trans. Graph.2