Abstract
Fuzheng Zhang, Xianwei Rong, Xiaoyan Yu, Huixin Qin
Abstract
Authors
Institutions
Provenance
crossref
Confidence 100%
openalex
Confidence 95%
datacite
Confidence 0%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Deep learning for LiDAR point clouds in autonomous driving: a review
10.1109/tnnls.2020.3015992 · 2021
3D object detection for autonomous driving: a survey
10.1016/j.patcog.2022.108796 · 2022
Unresolved referenced work
Kept as external metadata until matched
Pointnet: deep learning on point sets for 3D classification and segmentation
2017
Pointnet++: deep hierarchical feature learning on point sets in a metric space
2017
Pointrcnn: 3D object proposal generation and detection from point cloud
2019
3DSSD: point-based 3D single stage object detector
2020
Not all points are equal: learning highly efficient point-based detectors for 3D LiDAR point clouds
2022
Voxelnet: end-to-end learning for point cloud based 3D object detection
2018
3D semantic segmentation with submanifold sparse convolutional networks
2018
Second: sparsely embedded convolutional detection
10.3390/s18103337 · 2018
From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network
2021
PV-RCNN: point-voxel feature set abstraction for 3D object detection
2020
PV-rcnn++: point-voxel feature set abstraction with local vector representation for 3D object detection
10.1007/s11263-022-01710-9 · 2023
Voxel R-CNN: towards high performance voxel-based 3D object detection
2021
Pointpillars: fast encoders for object detection from point clouds
2019
Center-based 3D object detection and tracking
2021
Pillarnet: real-time and high-performance pillar-based 3D object detection
2022
Pillarnext: rethinking network designs for 3D object detection in LiDAR point clouds
2023
Voxelnext: fully sparse voxelnet for 3D object detection and tracking
2023
Embracing single stride 3D object detector with sparse transformer
2022
Dsvt: dynamic sparse voxel transformer with rotated sets
2023
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Pointpainting: sequential fusion for 3D object detection
2020
Transfusion: robust LiDAR-camera fusion for 3D object detection with transformers
2022
Bevfusion: multi-task multi-sensor fusion with unified bird’s-eye view representation
2023
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Point density-aware voxels for LiDAR 3D object detection
2022
Rsn: range sparse net for efficient, accurate LiDAR 3D object detection
2021
Dynamic learnable label assignment for indoor 3D object detection
10.1109/tcsvt.2025.3563083 · doi-reference
Svp: stratified vertical priors for LiDAR-based 3D object detection
10.1016/j.neucom.2025.131737 · doi-reference
Ascnet: 3D object detection from point cloud based on adaptive spatial context features
10.1016/j.neucom.2021.12.061 · doi-reference
SMS-net: sparse multi-scale voxel feature aggregation network for LiDAR-based 3D object detection
10.1016/j.neucom.2022.06.054 · doi-reference
Dvfenet: dual-branch voxel feature extraction network for 3D object detection
10.1016/j.neucom.2021.06.046 · doi-reference
Sarpnet: shape attention regional proposal network for LiDAR-based 3D object detection
10.1016/j.neucom.2019.09.086 · doi-reference
PV-rcnn++: point-voxel feature set abstraction with local vector representation for 3D object detection
10.1007/s11263-022-01710-9 · doi-reference
Second: sparsely embedded convolutional detection
10.3390/s18103337 · doi-reference
3D object detection for autonomous driving: a survey
10.1016/j.patcog.2022.108796 · doi-reference
Deep learning for LiDAR point clouds in autonomous driving: a review
10.1109/tnnls.2020.3015992 · doi-reference