Search Results for author:
Found 11 papers, 3 papers with code
UniPLV: Towards Label-Efficient Open-World 3D Scene Understanding by Regional Visual Language Supervision
We present UniPLV, a powerful framework that unifies point clouds, images and text in a single learning paradigm for open-world 3D scene understanding.
OLiDM: Object-aware LiDAR Diffusion Models for Autonomous Driving
To address the needs of object-aware tasks in 3D perception, we introduce OLiDM, a novel framework capable of generating high-fidelity LiDAR data at both the object and the scene levels.
StreetCrafter: Street View Synthesis with Controllable Video Diffusion Models
This paper aims to tackle the problem of photorealistic view synthesis from vehicle sensor data.
GaussianAD: Gaussian-Centric End-to-End Autonomous Driving
We initialize the scene with uniform 3D Gaussians and use surrounding-view images to progressively refine them to obtain the 3D Gaussian scene representation.
ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration
This is complemented by a progressive data update strategy designed to ensure high-quality rendering for more complex maneuvers.
Generalizing Motion Planners with Mixture of Experts for Autonomous Driving
These planners promise better generalizations on complicated and few-shot cases than previous methods.
UA-Track: Uncertainty-Aware End-to-End 3D Multi-Object Tracking
Secondly, we propose an Uncertainty-guided Query Denoising strategy to further enhance the training process.
Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation
Instead of randomly generating new data, we further design a sampling policy to let Delphi generate new data that are similar to those failure cases to improve the sample efficiency.
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models
A primary hurdle of autonomous driving in urban environments is understanding complex and long-tail scenarios, such as challenging road conditions and delicate human behaviors.
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving
Furthermore, there lack of well-formed retrieval datasets for effective evaluation.
Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting
Recent methods extend NeRF by incorporating tracked vehicle poses to animate vehicles, enabling photo-realistic view synthesis of dynamic urban street scenes.
