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Autonomous driving system: A comprehensive survey
J Zhao, W Zhao, B Deng, Z Wang, F Zhang… - Expert Systems with …, 2024 - Elsevier
Automation is increasingly at the forefront of transportation research, with the potential to
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
3D object detection for autonomous driving: A comprehensive survey
Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
Point transformer v3: Simpler faster stronger
This paper is not motivated to seek innovation within the attention mechanism. Instead it
focuses on overcoming the existing trade-offs between accuracy and efficiency within the …
focuses on overcoming the existing trade-offs between accuracy and efficiency within the …
Tri-perspective view for vision-based 3d semantic occupancy prediction
Modern methods for vision-centric autonomous driving perception widely adopt the bird's-
eye-view (BEV) representation to describe a 3D scene. Despite its better efficiency than …
eye-view (BEV) representation to describe a 3D scene. Despite its better efficiency than …
Voxelnext: Fully sparse voxelnet for 3d object detection and tracking
Abstract 3D object detectors usually rely on hand-crafted proxies, eg, anchors or centers,
and translate well-studied 2D frameworks to 3D. Thus, sparse voxel features need to be …
and translate well-studied 2D frameworks to 3D. Thus, sparse voxel features need to be …
Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving
X Tian, T Jiang, L Yun, Y Mao, H Yang… - Advances in …, 2023 - proceedings.neurips.cc
Robotic perception requires the modeling of both 3D geometry and semantics. Existing
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
Lmdrive: Closed-loop end-to-end driving with large language models
Despite significant recent progress in the field of autonomous driving modern methods still
struggle and can incur serious accidents when encountering long-tail unforeseen events …
struggle and can incur serious accidents when encountering long-tail unforeseen events …
Point transformer v2: Grouped vector attention and partition-based pooling
As a pioneering work exploring transformer architecture for 3D point cloud understanding,
Point Transformer achieves impressive results on multiple highly competitive benchmarks. In …
Point Transformer achieves impressive results on multiple highly competitive benchmarks. In …
Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction
The vision-based perception for autonomous driving has undergone a transformation from
the bird-eye-view (BEV) representations to the 3D semantic occupancy. Compared with the …
the bird-eye-view (BEV) representations to the 3D semantic occupancy. Compared with the …
Spherical transformer for lidar-based 3d recognition
LiDAR-based 3D point cloud recognition has benefited various applications. Without
specially considering the LiDAR point distribution, most current methods suffer from …
specially considering the LiDAR point distribution, most current methods suffer from …