5 papers
EVolSplat4D: Efficient Volume-based Gaussian Splatting for 4D Urban Scene Synthesis
Sheng Miao, Sijin Li, Pan Wang +5
Novel view synthesis (NVS) of static and dynamic urban scenes is essential for autonomous driving simulation, yet existing methods often struggle to balance reconstruction time wit…
Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation
Zhen Xu, Hongyu Zhou, Sida Peng +13
Depth estimation is a fundamental task in 3D computer vision, crucial for applications such as 3D reconstruction, free-viewpoint rendering, robotics, autonomous driving, and AR/VR…
UnIRe: Unsupervised Instance Decomposition for Dynamic Urban Scene Reconstruction
Yunxuan Mao, Rong Xiong, Yue Wang +1
Reconstructing and decomposing dynamic urban scenes is crucial for autonomous driving, urban planning, and scene editing. However, existing methods fail to perform instance-aware d…
EVolSplat: Efficient Volume-based Gaussian Splatting for Urban View Synthesis
Sheng Miao, Jiaxin Huang, Dongfeng Bai +6
Novel view synthesis of urban scenes is essential for autonomous driving-related applications.Existing NeRF and 3DGS-based methods show promising results in achieving photorealisti…
HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving
Hongyu Zhou, Longzhong Lin, Jiabao Wang +6
In the past few decades, autonomous driving algorithms have made significant progress in perception, planning, and control. However, evaluating individual components does not fully…