3 citations · 3 across the 5 of their papers we have counts for
5 papers
Explicit Layer Modeling for Video Object Insertion and Video Layer Decomposition
Kyujin Han, Seungjoo Shin, Sunghyun Cho
Most video editing systems still lack explicit layered video representations, limiting realistic compositing, object reuse, and consistent manipulation. This limitation is particul…
CoherentRaster: Efficient 3D Gaussian Splatting for Light Field Displays
Gyujin Sim, Seungjoo Shin, Hosung Jeon +3
Light field displays (LFDs) require rendering an interlaced image that encodes many view-dependent observations. This multi-view requirement introduces substantial computational ov…
Leveraging Learned Image Prior for 3D Gaussian Compression
Seungjoo Shin, Jaesik Park, Sunghyun Cho
Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering…
Learning Zero-Shot Subject-Driven Video Generation Using 1% Compute
Daneul Kim, Jingxu Zhang, Wonjoon Jin +4
Subject-driven video generation (SDV-Gen) aims to produce videos of a specific subject by adapting a pretrained video model, enabling personalized and application-driven content cr…
Locality-aware Gaussian Compression for Fast and High-quality Rendering
Seungjoo Shin, Jaesik Park, Sunghyun Cho
We present LocoGS, a locality-aware 3D Gaussian Splatting (3DGS) framework that exploits the spatial coherence of 3D Gaussians for compact modeling of volumetric scenes. To this en…