8 citations · 18 across the 16 of their papers we have counts for
5 papers · 1 filter
UniGaussian: Driving Scene Reconstruction from Multiple Camera Models via Unified Gaussian Representations
Yuan Ren, Guile Wu, Runhao Li +5
Urban scene reconstruction is crucial for real-world autonomous driving simulators. Although existing methods have achieved photorealistic reconstruction, they mostly focus on pinh…
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications
Eduardo R. Corral-Soto, Yang Liu, Tongtong Cao +2
In Autonomous Driving (AD) Perception, cyclists are considered safety-critical scene objects. Commonly used publicly-available AD datasets typically contain large amounts of car an…
Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusion
Shiqi Tan, Hamidreza Fazlali, Yixuan Xu +2
Range-View(RV)-based 3D point cloud segmentation is widely adopted due to its compact data form. However, RV-based methods fall short in providing robust segmentation for the occlu…
VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving
Yibo Liu, Zheyuan Yang, Guile Wu +5
Generating 3D vehicle assets from in-the-wild observations is crucial to autonomous driving. Existing image-to-3D methods cannot well address this problem because they learn genera…
AutoSplat: Constrained Gaussian Splatting for Autonomous Driving Scene Reconstruction
Mustafa Khan, Hamidreza Fazlali, Dhruv Sharma +4
Realistic scene reconstruction and view synthesis are essential for advancing autonomous driving systems by simulating safety-critical scenarios. 3D Gaussian Splatting excels in re…