55 citations · 84 across the 16 of their papers we have counts for
7 papers · 1 filter
StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Construction
Tianyuan Yuan, Yicheng Liu, Yue Wang +2
High-Definition (HD) maps are essential for the safety of autonomous driving systems. While existing techniques employ camera images and onboard sensors to generate vectorized high…
BEVScope: Enhancing Self-Supervised Depth Estimation Leveraging Bird's-Eye-View in Dynamic Scenarios
Yucheng Mao, Ruowen Zhao, Tianbao Zhang +1
Depth estimation is a cornerstone of perception in autonomous driving and robotic systems. The considerable cost and relatively sparse data acquisition of LiDAR systems have led to…
A Universal Semantic-Geometric Representation for Robotic Manipulation
Tong Zhang, Yingdong Hu, Hanchen Cui +2
Robots rely heavily on sensors, especially RGB and depth cameras, to perceive and interact with the world. RGB cameras record 2D images with rich semantic information while missing…
GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training
Xiaoyu Tian, Haoxi Ran, Yue Wang +1
This paper tries to address a fundamental question in point cloud self-supervised learning: what is a good signal we should leverage to learn features from point clouds without ann…
Programmatically Grounded, Compositionally Generalizable Robotic Manipulation
Renhao Wang, Jiayuan Mao, Joy Hsu +3
Robots operating in the real world require both rich manipulation skills as well as the ability to semantically reason about when to apply those skills. Towards this goal, recent w…
Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving
Xiaoyu Tian, Tao Jiang, Longfei Yun +5
Robotic perception requires the modeling of both 3D geometry and semantics. Existing methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details and…
Neural Map Prior for Autonomous Driving
Xuan Xiong, Yicheng Liu, Tianyuan Yuan +3
High-definition (HD) semantic maps are crucial in enabling autonomous vehicles to navigate urban environments. The traditional method of creating offline HD maps involves labor-int…