Research graph
References from SoftRangeBEV: Range-aware BEV feature learning for lightweight LiDAR-based 3D object detection. Local targets link to admitted publications; unresolved targets remain external evidence.
Deep learning for LiDAR point clouds in autonomous driving: a review
10.1109/tnnls.2020.3015992 · 2021 · External reference
3D object detection for autonomous driving: a survey
10.1016/j.patcog.2022.108796 · 2022 · External reference
Unresolved reference
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Pointnet: deep learning on point sets for 3D classification and segmentation
2017 · External reference
Pointnet++: deep hierarchical feature learning on point sets in a metric space
2017 · External reference
Pointrcnn: 3D object proposal generation and detection from point cloud
2019 · External reference
3DSSD: point-based 3D single stage object detector
2020 · External reference
Not all points are equal: learning highly efficient point-based detectors for 3D LiDAR point clouds
2022 · External reference
Voxelnet: end-to-end learning for point cloud based 3D object detection
2018 · External reference
3D semantic segmentation with submanifold sparse convolutional networks
2018 · External reference
Second: sparsely embedded convolutional detection
10.3390/s18103337 · 2018 · External reference
From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network
2021 · External reference
PV-RCNN: point-voxel feature set abstraction for 3D object detection
2020 · External reference
PV-rcnn++: point-voxel feature set abstraction with local vector representation for 3D object detection
10.1007/s11263-022-01710-9 · 2023 · External reference
Voxel R-CNN: towards high performance voxel-based 3D object detection
2021 · External reference
Pointpillars: fast encoders for object detection from point clouds
2019 · External reference
Center-based 3D object detection and tracking
2021 · External reference
Pillarnet: real-time and high-performance pillar-based 3D object detection
2022 · External reference
Pillarnext: rethinking network designs for 3D object detection in LiDAR point clouds
2023 · External reference
Voxelnext: fully sparse voxelnet for 3D object detection and tracking
2023 · External reference
Embracing single stride 3D object detector with sparse transformer
2022 · External reference
Dsvt: dynamic sparse voxel transformer with rotated sets
2023 · External reference
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Pointpainting: sequential fusion for 3D object detection
2020 · External reference
Transfusion: robust LiDAR-camera fusion for 3D object detection with transformers
2022 · External reference
Bevfusion: multi-task multi-sensor fusion with unified bird’s-eye view representation
2023 · External reference
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Point density-aware voxels for LiDAR 3D object detection
2022 · External reference
Rsn: range sparse net for efficient, accurate LiDAR 3D object detection
2021 · External reference
Rangedet: in defense of range view for LiDAR-based 3D object detection
2021 · External reference
Rangeioudet: range image based real-time 3D object detector optimized by intersection over Union
2021 · External reference
Sarpnet: shape attention regional proposal network for LiDAR-based 3D object detection
10.1016/j.neucom.2019.09.086 · 2020 · External reference
Dvfenet: dual-branch voxel feature extraction network for 3D object detection
10.1016/j.neucom.2021.06.046 · 2021 · External reference
SMS-net: sparse multi-scale voxel feature aggregation network for LiDAR-based 3D object detection
10.1016/j.neucom.2022.06.054 · 2022 · External reference
Ascnet: 3D object detection from point cloud based on adaptive spatial context features
10.1016/j.neucom.2021.12.061 · 2022 · External reference
Svp: stratified vertical priors for LiDAR-based 3D object detection
10.1016/j.neucom.2025.131737 · 2026 · External reference
Towards accurate 3D object detection in adverse weather by leveraging 4D radar for LiDAR geometry enhancement
2026 · External reference
Dynamic learnable label assignment for indoor 3D object detection
10.1109/tcsvt.2025.3563083 · 2025 · External reference
SPE-bevhead: rethinking the detection head design for bird’s-eye-view object detection
2026 · External reference
Are we ready for autonomous driving? The kitti vision benchmark suite
2012 · External reference
nuscenes: a multimodal dataset for autonomous driving
2020 · External reference
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Adam: a method for stochastic optimization
2015 · External reference
Super-convergence: very fast training of neural networks using large learning rates
2019 · External reference
Unresolved reference
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PV-rcnn++: point-voxel feature set abstraction with local vector representation for 3D object detection
10.1007/s11263-022-01710-9 · ExternalCitation · doi-reference
Sarpnet: shape attention regional proposal network for LiDAR-based 3D object detection
10.1016/j.neucom.2019.09.086 · ExternalCitation · doi-reference
Dvfenet: dual-branch voxel feature extraction network for 3D object detection
10.1016/j.neucom.2021.06.046 · ExternalCitation · doi-reference
Ascnet: 3D object detection from point cloud based on adaptive spatial context features
10.1016/j.neucom.2021.12.061 · ExternalCitation · doi-reference
SMS-net: sparse multi-scale voxel feature aggregation network for LiDAR-based 3D object detection
10.1016/j.neucom.2022.06.054 · ExternalCitation · doi-reference
Svp: stratified vertical priors for LiDAR-based 3D object detection
10.1016/j.neucom.2025.131737 · ExternalCitation · doi-reference
3D object detection for autonomous driving: a survey
10.1016/j.patcog.2022.108796 · ExternalCitation · doi-reference
Dynamic learnable label assignment for indoor 3D object detection
10.1109/tcsvt.2025.3563083 · ExternalCitation · doi-reference
Deep learning for LiDAR point clouds in autonomous driving: a review
10.1109/tnnls.2020.3015992 · ExternalCitation · doi-reference
Second: sparsely embedded convolutional detection
10.3390/s18103337 · ExternalCitation · doi-reference
