7 papers
TIGaussian: Disentangle Gaussians for Spatial-Awared Text-Image-3D Alignment
Jiarun Liu, Qifeng Chen, Yiru Zhao +3
While visual-language models have profoundly linked features between texts and images, the incorporation of 3D modality data, such as point clouds and 3D Gaussians, further enables…
LiDAR-GS++:Improving LiDAR Gaussian Reconstruction via Diffusion Priors
Qifeng Chen, Jiarun Liu, Rengan Xie +5
Recent GS-based rendering has made significant progress for LiDAR, surpassing Neural Radiance Fields (NeRF) in both quality and speed. However, these methods exhibit artifacts in e…
LiDAR-GS:Real-time LiDAR Re-Simulation using Gaussian Splatting
Qifeng Chen, Sheng Yang, Sicong Du +4
We present LiDAR-GS, a Gaussian Splatting (GS) method for real-time, high-fidelity re-simulation of LiDAR scans in public urban road scenes. Recent GS methods proposed for cameras…
GS-RoadPatching: Inpainting Gaussians via 3D Searching and Placing for Driving Scenes
Guo Chen, Jiarun Liu, Sicong Du +5
This paper presents GS-RoadPatching, an inpainting method for driving scene completion by referring to completely reconstructed regions, which are represented by 3D Gaussian Splatt…
RGE-GS: Reward-Guided Expansive Driving Scene Reconstruction via Diffusion Priors
Sicong Du, Jiarun Liu, Qifeng Chen +3
A single-pass driving clip frequently results in incomplete scanning of the road structure, making reconstructed scene expanding a critical requirement for sensor simulators to eff…
Industrial-Grade Sensor Simulation via Gaussian Splatting: A Modular Framework for Scalable Editing and Full-Stack Validation
Xianming Zeng, Sicong Du, Qifeng Chen +13
Sensor simulation is pivotal for scalable validation of autonomous driving systems, yet existing Neural Radiance Fields (NeRF) based methods face applicability and efficiency chall…