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20232026
most citedSeparable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation

8 citations · 21 across the 20 of their papers we have counts for

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5 papers · 1 filter

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.CV2025

Uni3R: Unified 3D Reconstruction and Semantic Understanding via Generalizable Gaussian Splatting from Unposed Multi-View Images

Xiangyu Sun, Haoyi Jiang, Liu Liu +8

Reconstructing and semantically interpreting 3D scenes from sparse 2D views remains a fundamental challenge in computer vision. Conventional methods often decouple semantic underst…

cs.CV2025

iLRM: An Iterative Large 3D Reconstruction Model

Gyeongjin Kang, Seungtae Nam, Seungkwon Yang +4

Feed-forward 3D modeling has emerged as a promising approach for rapid and high-quality 3D reconstruction. In particular, directly generating explicit 3D representations, such as 3…

cs.CV2025

Hybrid 3D-4D Gaussian Splatting for Fast Dynamic Scene Representation

Seungjun Oh, Younggeun Lee, Hyejin Jeon +1

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these,…

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…