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Niv-Ssd: Neighbor Iou-Voting Single-Stage Object Detector from Point Cloud

https://doi.org/10.2139/ssrn.4715282
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inferredcites →https://doi.org/10.1007/978-3-030-01264-9_48openalex-extracted
Acquisition of Localization Confidence for Accurate Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-01270-0_39openalex-extracted
Deep Continuous Fusion for Multi-sensor 3D Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-58583-9_43openalex-extracted
3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-view Spatial Feature Fusion for 3D Object Detection
inferredcites →https://doi.org/10.1007/978-3-030-58589-1_5openalex-extracted
Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots
inferredcites →https://doi.org/10.1016/j.imavis.2020.103911openalex-extracted
IoU-aware single-stage object detector for accurate localization
inferredcites →https://doi.org/10.1016/j.neucom.2021.12.061openalex-extracted
ASCNet: 3D object detection from point cloud based on adaptive spatial context features
inferredcites →https://doi.org/10.1016/j.neucom.2022.06.054openalex-extracted
SMS-Net: Sparse multi-scale voxel feature aggregation network for LiDAR-based 3D object detection
inferredcites →https://doi.org/10.1016/j.patcog.2021.107884openalex-extracted
3D-CenterNet: 3D object detection network for point clouds with center estimation priority
inferredcites →https://doi.org/10.1016/j.patcog.2022.108524openalex-extracted
BADet: Boundary-Aware 3D Object Detection from Point Clouds
inferredcites →https://doi.org/10.1016/j.patcog.2022.108684openalex-extracted
Spatial information enhancement network for 3D object detection from point cloud
inferredcites →https://doi.org/10.1109/3dv.2019.00019openalex-extracted
IoU Loss for 2D/3D Object Detection
inferredcites →https://doi.org/10.1109/cvpr.1993.341010openalex-extracted
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.16openalex-extracted
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.691openalex-extracted
Multi-view 3D Object Detection Network for Autonomous Driving
inferredcites →https://doi.org/10.1109/cvpr.2018.00472openalex-extracted
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2018.00719openalex-extracted
Improving Object Localization with Fitness NMS and Bounded IoU Loss
inferredcites →https://doi.org/10.1109/cvpr.2019.00086openalex-extracted
PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud
inferredcites →https://doi.org/10.1109/cvpr.2019.00657openalex-extracted
Mask Scoring R-CNN
inferredcites →https://doi.org/10.1109/cvpr.2019.00752openalex-extracted
Multi-Task Multi-Sensor Fusion for 3D Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2019.01298openalex-extracted
PointPillars: Fast Encoders for Object Detection From Point Clouds
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00178openalex-extracted
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00252openalex-extracted
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01105openalex-extracted
3DSSD: Point-Based 3D Single Stage Object Detector
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01334openalex-extracted
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01161openalex-extracted
Center-based 3D Object Detection and Tracking
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01838openalex-extracted
Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds
inferredcites →https://doi.org/10.1109/iccv.2019.00204openalex-extracted
STD: Sparse-to-Dense 3D Object Detector for Point Cloud
inferredcites →https://doi.org/10.1109/iccv.2019.00972openalex-extracted
FCOS: Fully Convolutional One-Stage Object Detection
inferredcites →https://doi.org/10.1109/iros.2018.8594049openalex-extracted
Joint 3D Proposal Generation and Object Detection from View Aggregation
inferredcites →https://doi.org/10.1109/iros40897.2019.8968513openalex-extracted
Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
inferredcites →https://doi.org/10.1109/tits.2023.3267665openalex-extracted
SVDnet: Singular Value Control and Distance Alignment Network for 3D Object Detection
inferredcites →https://doi.org/10.1109/tpami.2020.2977026openalex-extracted
From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network
inferredcites →https://doi.org/10.1177/0278364913491297openalex-extracted
Vision meets robotics: The KITTI dataset
inferredcites →https://doi.org/10.1609/aaai.v35i2.16207openalex-extracted
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
inferredcites →https://doi.org/10.1609/aaai.v35i4.16470openalex-extracted
CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud
inferredcites →https://doi.org/10.1609/aaai.v36i3.20194openalex-extracted
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
inferredcites →https://doi.org/10.48550/arxiv.1612.00593openalex-extracted
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1706.02413openalex-extracted
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
inferredcites →https://doi.org/10.48550/arxiv.1908.09492openalex-extracted
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
inferredcites →https://doi.org/10.48550/arxiv.2006.04388openalex-extracted
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
inferredcites →https://doi.org/10.48550/arxiv.2106.11037openalex-extracted
One Million Scenes for Autonomous Driving: ONCE Dataset
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