1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2026
AdaGScale: Viewpoint-Adaptive Gaussian Scaling in 3D Gaussian Splatting to Reduce Gaussian-Tile Pairs
Joongho Jo, Hyerin Lim, Hanjun Choi +1
Reducing the number of Gaussian-tile pairs is one of the most promising approaches to improve 3D Gaussian Splatting (3D-GS) rendering speed on GPUs. However, the importance differe…
cs.AR2025
GS-TG: 3D Gaussian Splatting Accelerator with Tile Grouping for Reducing Redundant Sorting while Preserving Rasterization Efficiency
Joongho Jo, Jongsun Park
3D Gaussian Splatting (3D-GS) has emerged as a promising alternative to neural radiance fields (NeRF) as it offers high speed as well as high image quality in novel view synthesis.…
cs.CV2024★ 1 cited
Identifying Unnecessary 3D Gaussians using Clustering for Fast Rendering of 3D Gaussian Splatting
Joongho Jo, Hyeongwon Kim, Jongsun Park
3D Gaussian splatting (3D-GS) is a new rendering approach that outperforms the neural radiance field (NeRF) in terms of both speed and image quality. 3D-GS represents 3D scenes by…