3 papers
cs.RO2024
THUD++: Large-Scale Dynamic Indoor Scene Dataset and Benchmark for Mobile Robots
Zeshun Li, Fuhao Li, Wanting Zhang +4
Most existing mobile robotic datasets primarily capture static scenes, limiting their utility for evaluating robotic performance in dynamic environments. To address this, we presen…
cs.CV2024
2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction
Wanting Zhang, Haodong Xiang, Zhichao Liao +3
The reconstruction of indoor scenes remains challenging due to the inherent complexity of spatial structures and the prevalence of textureless regions. Recent advancements in 3D Ga…
cs.CV2024
Fine-detailed Neural Indoor Scene Reconstruction using multi-level importance sampling and multi-view consistency
Xinghui Li, Yuchen Ji, Xiansong Lai +1
Recently, neural implicit 3D reconstruction in indoor scenarios has become popular due to its simplicity and impressive performance. Previous works could produce complete results l…