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cs.CV2026

ACA-GS: Adaptive-Capacity Anchored Gaussian Splatting for Compact Dynamic Radiance Fields

Seunghyeon Song, Joo Chan Lee, Chanung Park +4

Recent advances in 4D Gaussian Splatting (4DGS) enable high-fidelity, real-time spatiotemporal rendering, but expose a fundamental trade-off between motion expressiveness and stora…

cs.CV2025

Optimized Minimal 3D Gaussian Splatting

Joo Chan Lee, Jong Hwan Ko, Eunbyung Park

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D sce…

cs.CV2025

Optimized Minimal 4D Gaussian Splatting

Minseo Lee, Byeonghyeon Lee, Lucas Yunkyu Lee +7

4D Gaussian Splatting has emerged as a new paradigm for dynamic scene representation, enabling real-time rendering of scenes with complex motions. However, it faces a major challen…

cs.CV2024

Compact 3D Gaussian Splatting for Static and Dynamic Radiance Fields

Joo Chan Lee, Daniel Rho, Xiangyu Sun +2

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rende…

cs.CV2024

Continuous Memory Representation for Anomaly Detection

Joo Chan Lee, Taejune Kim, Eunbyung Park +2

There have been significant advancements in anomaly detection in an unsupervised manner, where only normal images are available for training. Several recent methods aim to detect a…

cs.CV2024

F-3DGS: Factorized Coordinates and Representations for 3D Gaussian Splatting

Xiangyu Sun, Joo Chan Lee, Daniel Rho +3

The neural radiance field (NeRF) has made significant strides in representing 3D scenes and synthesizing novel views. Despite its advancements, the high computational costs of NeRF…