4 papers
DriveMamba: Task-Centric Scalable State Space Model for Efficient End-to-End Autonomous Driving
Haisheng Su, Wei Wu, Feixiang Song +3
Recent advances towards End-to-End Autonomous Driving (E2E-AD) have been often devoted on integrating modular designs into a unified framework for joint optimization e.g. UniAD, wh…
FreqPDE: Rethinking Positional Depth Embedding for Multi-View 3D Object Detection Transformers
Haisheng Su, Junjie Zhang, Feixiang Song +4
Detecting 3D objects accurately from multi-view 2D images is a challenging yet essential task in the field of autonomous driving. Current methods resort to integrating depth predic…
UniMamba: Unified Spatial-Channel Representation Learning with Group-Efficient Mamba for LiDAR-based 3D Object Detection
Xin Jin, Haisheng Su, Kai Liu +4
Recent advances in LiDAR 3D detection have demonstrated the effectiveness of Transformer-based frameworks in capturing the global dependencies from point cloud spaces, which serial…
EgoFSD: Ego-Centric Fully Sparse Paradigm with Uncertainty Denoising and Iterative Refinement for Efficient End-to-End Self-Driving
Haisheng Su, Wei Wu, Zhenjie Yang +1
Current End-to-End Autonomous Driving (E2E-AD) methods resort to unifying modular designs for various tasks (e.g. perception, prediction and planning). Although optimized with a fu…