55 citations · 84 across the 16 of their papers we have counts for
11 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…
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…
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…
PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework
Bowen Li, Ziyuan Huang, Junjie Ye +4
Visual object tracking is essential to intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world…
VectorFlow: Combining Images and Vectors for Traffic Occupancy and Flow Prediction
Xin Huang, Xiaoyu Tian, Junru Gu +2
Predicting future behaviors of road agents is a key task in autonomous driving. While existing models have demonstrated great success in predicting marginal agent future behaviors,…
ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queries
Junru Gu, Chenxu Hu, Tianyuan Zhang +4
Perception and prediction are two separate modules in the existing autonomous driving systems. They interact with each other via hand-picked features such as agent bounding boxes a…
Beyond Visual Field of View: Perceiving 3D Environment with Echoes and Vision
Lingyu Zhu, Esa Rahtu, Hang Zhao
This paper focuses on perceiving and navigating 3D environments using echoes and RGB image. In particular, we perform depth estimation by fusing RGB image with echoes, received fro…
R4D: Utilizing Reference Objects for Long-Range Distance Estimation
Yingwei Li, Tiffany Chen, Maya Kabkab +4
Estimating the distance of objects is a safety-critical task for autonomous driving. Focusing on short-range objects, existing methods and datasets neglect the equally important lo…
Egocentric Prediction of Action Target in 3D
Yiming Li, Ziang Cao, Andrew Liang +4
We are interested in anticipating as early as possible the target location of a person's object manipulation action in a 3D workspace from egocentric vision. It is important in fie…