2 citations · 2 across the 9 of their papers we have counts for
10 papers
Trajectory Forcing: Structure-First Generation with Controllable Semantic Trajectories
Merve Kocabas, Gege Gao, Bernhard Schölkopf +1
Diffusion and flow-based generative models produce strong images, yet their controllability remains largely endpoint-centric: users specify conditions and receive final outputs, wh…
World Engine: Towards the Era of Post-Training for Autonomous Driving
Tianyu Li, Li Chen, Caojun Wang +16
Autonomous vehicles must operate safely in the real world, where errors can have severe consequences. Although modern end-to-end driving policies excel in routine scenarios, their…
123D: Unifying Multi-Modal Autonomous Driving Data at Scale
Daniel Dauner, Valentin Charraut, Bastian Berle +10
The pursuit of autonomous driving has produced one of the richest sensor data collections in all of robotics. However, its scale and diversity remain largely untapped. Each dataset…
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…
PrITTI: Primitive-based Generation of Controllable and Editable 3D Semantic Urban Scenes
Christina Ourania Tze, Daniel Dauner, Yiyi Liao +2
Existing approaches to 3D semantic urban scene generation predominantly rely on voxel-based representations, which are bound by fixed resolution, challenging to edit, and memory-in…
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…
UrbanCAD: Towards Highly Controllable and Photorealistic 3D Vehicles for Urban Scene Simulation
Yichong Lu, Yichi Cai, Shangzhan Zhang +5
Photorealistic 3D vehicle models with high controllability are essential for autonomous driving simulation and data augmentation. While handcrafted CAD models provide flexible cont…
Efficient Depth-Guided Urban View Synthesis
Sheng Miao, Jiaxin Huang, Dongfeng Bai +4
Recent advances in implicit scene representation enable high-fidelity street view novel view synthesis. However, existing methods optimize a neural radiance field for each scene, r…
HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting
Hongyu Zhou, Jiahao Shao, Lu Xu +6
Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel vie…