1 citations · 1 across the 2 of their papers we have counts for
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.RO2024★ 1 cited
Mobile Robot Oriented Large-Scale Indoor Dataset for Dynamic Scene Understanding
Yifan Tang, Cong Tai, Fangxing Chen +5
Most existing robotic datasets capture static scene data and thus are limited in evaluating robots' dynamic performance. To address this, we present a mobile robot oriented large-s…
cs.CV2024
GaussianRoom: Improving 3D Gaussian Splatting with SDF Guidance and Monocular Cues for Indoor Scene Reconstruction
Haodong Xiang, Xinghui Li, Kai Cheng +5
Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data. Although 3D Gaussian Splatting (3DGS) has recently demonstrated high-qu…