Paper (Lidar-based method)

• End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds paper
• Vehicle Detection from 3D Lidar Using Fully Convolutional Network(baidu) paper
• VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection paper
• Object Detection and Classification in Occupancy Grid Maps using Deep Convolutional Networks paper
• RT3D: Real-Time 3-D Vehicle Detection in LiDAR Point Cloud for Autonomous Driving paper
• BirdNet: a 3D Object Detection Framework from LiDAR information paper
• LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDAR paper
• HDNET: Exploit HD Maps for 3D Object Detection paper
• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation paper
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space paper
• IPOD: Intensive Point-based Object Detector for Point Cloud paper
• PIXOR: Real-time 3D Object Detection from Point Clouds paper
• DepthCN: Vehicle Detection Using 3D-LIDAR and ConvNet paper
• Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds paper
• STD: Sparse-to-Dense 3D Object Detector for Point Cloud paper
• Fast Point R-CNN paper
• StarNet: Targeted Computation for Object Detection in Point Clouds paper
• Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection paper
• LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving paper
• FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds paper
• Part-A^2 Net: 3D Part-Aware and Aggregation Neural Network for Object Detection from Point Cloud paper
• PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud paper
• Complex-YOLO: Real-time 3D Object Detection on Point Clouds paper
• YOLO4D: A ST Approach for RT Multi-object Detection and Classification from LiDAR Point Clouds paper
• YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud paper
• Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud paper
• Pillar-based Object Detection for Autonomous Driving (ECCV2020) paper
• EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection(ECCV2020) paper
• Multi-Echo LiDAR for 3D Object Detection(ICCV2021) paper
• LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector(ICCV2021) paper
• SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation(ICCV2021) paper
• Structure Aware Single-stage 3D Object Detection from Point Cloud（CVPR2020) paper code
• MLCVNet: Multi-Level Context VoteNet for 3D Object Detection（CVPR2020) paper code
• 3DSSD: Point-based 3D Single Stage Object Detector（CVPR2020） paper code
• LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention（CVPR2020） paper code
• PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection(CVPR2020) paper code
• Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud（CVPR2020） paper code
• MLCVNet: Multi-Level Context VoteNet for 3D Object Detection（CVPR2020） paper
• Density Based Clustering for 3D Object Detection in Point Clouds（CVPR2020） paper
• What You See is What You Get: Exploiting Visibility for 3D Object Detection（CVPR2020) paper
• PointPainting: Sequential Fusion for 3D Object Detection(CVPR2020) paper
• HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection（CVPR2020) paper
• LiDAR R-CNN: An Efficient and Universal 3D Object Detector（CVPR2021) paper
• Center-based 3D Object Detection and Tracking(CVPR2021) paper
• 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection(CVPR2021) paper
• Embracing Single Stride 3D Object Detector with Sparse Transformer(CVPR2022) paper, code
• Point Density-Aware Voxels for LiDAR 3D Object Detection(CVPR2022) paper, code
• A Unified Query-based Paradigm for Point Cloud Understanding(CVPR2022) paper
• Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds(CVPR2022) paper, code
• Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds(CVPR2022) paper, code
• Back To Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement(CVPR2022) paper, code
• Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds(CVPR2022) paper, code
• BoxeR: Box-Attention for 2D and 3D Transformers(CVPR2022) paper, code, 中文介绍
• Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes(CVPR2022) paper, code
• DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection(CVPR2022) paper, code
• TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers. (CVPR2022) paper, code
• Point2Seq: Detecting 3D Objects as Sequences. (CVPR2022) paper, code
• CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection(CVPR2022) paper
• LiDAR Snowfall Simulation for Robust 3D Object Detection(CVPR2022) paper, code
• Unified Transformer Tracker for Object Trackin