12 papers
The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms
Lingdong Kong, Shaoyuan Xie, Zeying Gong +135
Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under…
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…
LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences
Ao Liang, Youquan Liu, Yu Yang +5
Generative world models have become essential data engines for autonomous driving, yet most existing efforts focus on videos or occupancy grids, overlooking the unique LiDAR proper…
Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning
Buzhen Huang, Chen Li, Chongyang Xu +4
Due to visual ambiguities and inter-person occlusions, existing human pose estimation methods cannot recover plausible close interactions from in-the-wild videos. Even state-of-the…