15 papers
Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future
Tianshuai Hu, Xiaolu Liu, Song Wang +17
Autonomous driving has long relied on modular "Perception-Decision-Action" pipelines, where hand-crafted interfaces and rule-based components often break down in complex or long-ta…
Learning to Remove Lens Flare in Event Camera
Haiqian Han, Lingdong Kong, Jianing Li +7
Event cameras have the potential to revolutionize vision systems with their high temporal resolution and dynamic range, yet they remain susceptible to lens flare, a fundamental opt…
3EED: Ground Everything Everywhere in 3D
Rong Li, Yuhao Dong, Tianshuai Hu +7
Visual grounding in 3D is the key for embodied agents to localize language-referred objects in open-world environments. However, existing benchmarks are limited to indoor focus, si…
Learning to Generate 4D LiDAR Sequences
Ao Liang, Youquan Liu, Yu Yang +5
While generative world models have advanced video and occupancy-based data synthesis, LiDAR generation remains underexplored despite its importance for accurate 3D perception. Exte…
Visual Grounding from Event Cameras
Lingdong Kong, Dongyue Lu, Ao Liang +6
Event cameras capture changes in brightness with microsecond precision and remain reliable under motion blur and challenging illumination, offering clear advantages for modeling hi…
La La LiDAR: Large-Scale Layout Generation from LiDAR Data
Youquan Liu, Lingdong Kong, Weidong Yang +5
Controllable generation of realistic LiDAR scenes is crucial for applications such as autonomous driving and robotics. While recent diffusion-based models achieve high-fidelity LiD…