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Bev-Cam3d: A Unified Bird's Eye View Architecture (Bev) for Multiple Monocular Cameras (Cam) and Three-Dimensional (3d) Point Clouds

https://doi.org/10.2139/ssrn.4772696
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Inverse perspective mapping simplifies optical flow computation and obstacle detection
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PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
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Geometric modeling using octree encoding
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Data-driven 3D Voxel Patterns for object category recognition
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Monocular 3D Object Detection for Autonomous Driving
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Monocular Depth Estimation Using Neural Regression Forest
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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3D Bounding Box Estimation Using Deep Learning and Geometry
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Multi-view 3D Object Detection Network for Autonomous Driving
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4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
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Occupancy Networks: Learning 3D Reconstruction in Function Space
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Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
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Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction
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PointPillars: Fast Encoders for Object Detection From Point Clouds
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PointPainting: Sequential Fusion for 3D Object Detection
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PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
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Predicting Semantic Map Representations From Images Using Pyramid Occupancy Networks
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nuScenes: A Multimodal Dataset for Autonomous Driving
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Structure Aware Single-Stage 3D Object Detection From Point Cloud
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Categorical Depth Distribution Network for Monocular 3D Object Detection
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Center-based 3D Object Detection and Tracking
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Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-view Transformation
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TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
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Vision Transformer with Deformable Attention
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Cross-view Transformers for real-time Map-view Semantic Segmentation
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BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision
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BEV-Guided Multi-Modality Fusion for Driving Perception
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SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
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Attention Augmented Convolutional Networks
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CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
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NEAT: Neural Attention Fields for End-to-End Autonomous Driving
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PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
inferredcites →https://doi.org/10.1109/iccv51070.2023.00637openalex-extracted
FB-BEV: BEV Representation from Forward-Backward View Transformations
inferredcites →https://doi.org/10.1109/iccv51070.2023.00865openalex-extracted
OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
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Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications
inferredcites →https://doi.org/10.1109/icra46639.2022.9812383openalex-extracted
HDMapNet: An Online HD Map Construction and Evaluation Framework
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BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
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VoxNet: A 3D Convolutional Neural Network for real-time object recognition
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Joint 3D Proposal Generation and Object Detection from View Aggregation
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Patchwork++: Fast and Robust Ground Segmentation Solving Partial Under-Segmentation Using 3D Point Cloud
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BirdNet+: End-to-End 3D Object Detection in LiDAR Bird’s Eye View
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A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird’s Eye View
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UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities
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Fast segmentation of 3D point clouds for ground vehicles
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Robust IMU/GPS/VO Integration for Vehicle Navigation in GNSS Degraded Urban Areas
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LiDAR Point Clouds to 3-D Urban Models$:$ A Review
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Voxel-Based Extraction and Classification of 3-D Pole-Like Objects From Mobile LiDAR Point Cloud Data
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Bird’s-Eye-View Panoptic Segmentation Using Monocular Frontal View Images
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Bi-Mapper: Holistic BEV Semantic Mapping for Autonomous Driving
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Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
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Recent Advancements in End-to-End Autonomous Driving Using Deep Learning: A Survey
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3D Convolutional Neural Networks for Human Action Recognition
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Deep Learning for 3D Point Clouds: A Survey
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Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline
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Vision-Centric BEV Perception: A Survey
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SBEVNet: End-to-End Deep Stereo Layout Estimation
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Object Detection for Autonomous Driving
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MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization
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Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process
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SECOND: Sparsely Embedded Convolutional Detection
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Deep Learning on Point Clouds and Its Application: A Survey
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CFNet: LiDAR-Camera Registration Using Calibration Flow Network
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Exploiting Generative AI to Scale up Intelligent Tutoring Systems
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Building a Balanced k-d Tree in O(kn log n) Time
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Spatial Transformer Networks
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
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Attention Is All You Need
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Complex-YOLO: Real-time 3D Object Detection on Point Clouds
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Learning Translation Invariance in CNNs
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FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras
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DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
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Multimodal Virtual Point 3D Detection
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BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
inferredcites →https://doi.org/10.48550/arxiv.2203.11496openalex-extracted
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
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BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection
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BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
inferredcites →https://doi.org/10.48550/arxiv.2205.13790openalex-extracted
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
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Unifying Voxel-based Representation with Transformer for 3D Object Detection
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Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer
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FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation
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A REVIEW OF POINT CLOUDS SEGMENTATION AND CLASSIFICATION ALGORITHMS
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