This is a repository for Bird's Eye View Perception, including 3D object detection, segmentation, online-mapping and occupancy prediction.

- 2023.05.09: An initial version of recent papers or projects.
- 2023.05.12: Adding paper for 3D object detection.
- 2023.05.14: Adding paper for BEV segmentation, HD-map construction, Occupancy prediction and motion planning.

• Survey
• 3D Object Detection
  • Radar Lidar
  • Radar Camera
  • Lidar Camera
  • Lidar
  • Monocular
  • Multiple Camera
• BEV Segmentation
  • Lidar Camera
  • Lidar
  • Monocular
  • Multiple Camera
• Tracking
• Perception Prediction Planning
  • Monocular
  • Multiple Camera
• Mapping
  • Lidar
  • Lidar Camera
  • Monocular
  • Multiple Camera
• Locate
• Occupancy Prediction
  • Occupancy Challenge
• Challenge
• Dataset
• World Model
• Other

• Vision-Centric BEV Perception: A Survey (Arxiv 2022)[Paper] [Github]
• Delving into the Devils of Bird’s-eye-viewPerception: A Review, Evaluation and Recipe (Arxiv 2022) [Paper] [Github]

• RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection System (Arxiv 2023) [Paper]
• Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D DynamicObject Detection (CVPR 2023) [paper] [Github]
• MaskBEV: Joint Object Detection and Footprint Completion for Bird’s-eye View 3D Point Clouds (IORS 2023) [Paper] [Github]
• LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion (Arxiv 2023) [Paper]

• CRAFT: Camera-Radar 3D Object Detectionwith Spatio-Contextual Fusion Transformer (Arxiv 2022) [Paper]
• RadSegNet: A Reliable Approach to Radar Camera Fusion (Arxiv 2022) [paper]
• Bridging the View Disparity of Radar and Camera Features for Multi-modal Fusion 3D Object Detection (IEEE TIV 2023) [Paper]
• CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception (ICLRW 2023) [Paper]
• RC-BEVFusion: A Plug-In Module for Radar-CameraBird’s Eye View Feature Fusion (Arxiv 2023) [Paper]

• Semantic bevfusion: rethink lidar-camera fusion in unified bird’s-eye view representation for 3d object detection (Arxiv 2022) [Paper]
• Sparse Dense Fusion for 3D Object Detection (Arxiv 2023) [Paper]
• EA-BEV: Edge-aware Bird' s-Eye-View Projector for 3D Object Detection (Arxiv 2023) [Paper] [Github]
• MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection (CVPR 2023) [paper] [Github]
• FULLER: Unified Multi-modality Multi-task 3D Perception via Multi-level Gradient Calibration (Arxiv 2023) [Paper]
• Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection (Arxiv 2023) [paper]
• SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection (ICCV 2023) [Paper] [Github]
• 3DifFusionDet: Diffusion Model for 3D Object Detection with Robust LiDAR-Camera Fusion (Arxiv 2023) [Paper]
• FUSIONVIT: HIERARCHICAL 3D OBJECT DETECTION VIA LIDAR-CAMERA VISION TRANSFORMER FUSION (Arxiv 2023) [paper]
• Lift-Attend-Splat: Bird's-eye-view camera-lidar fusion using transformers (Arxiv 2023) [Paper]

• MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object Detection (AAAI 2023)[paper][Github]
• PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection (Arxiv 2023) [Paper]
• V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection (Arxiv 2023) [Paper]

• Learning 2D to 3D Lifting for Object Detection in 3Dfor Autonomous Vehicles (IROS 2019) [Paper] [Project Page
• Orthographic Feature Transform for Monocular 3D Object Detection (BMVC 2019) [Paper] [Github]
• BEV-MODNet: Monocular Camera-based Bird's Eye View Moving Object Detection for Autonomous Driving (ITSC 2021) [Paper] [Project Page]
• Categorical Depth Distribution Network for Monocular 3D Object Detection (CVPR 2021) [Paper] [Github]
• PersDet: Monocular 3D Detection in Perspective Bird’s-Eye-View (Arxiv 2022) [Paper]
• Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving (CVPR 2022) [Paper]
• Monocular 3D Object Detection with Depth from Motion (ECCV 2022) [paper][Github]
• MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection (ICCV 2023) [Paper] [Github]
• S3-MonoDETR: Supervised Shape&Scale-perceptive Deformable Transformer for Monocular 3D Object Detection (Arxiv 2023) [Paper] [Github]
• MonoGAE: Roadside Monocular 3D Object Detection with Ground-Aware Embeddings (Arxiv 2023) [Paper]
• YOLO-BEV: Generating Bird's-Eye View in the Same Way as 2D Object Detection (Arxiv 2023) [Paper]
• UniMODE: Unified Monocular 3D Object Detection (CVPR 2024) [Paper]
• Scalable Vision-Based 3D Object Detection and Monocular Depth Estimation for Autonomous Driving (Arxuv 2024) [paper] [Github]
• UniMODE: Unified Monocular 3D Object Detection (CVPR 2024) [Paper]

• Object DGCNN: 3D Object Detection using Dynamic Graphs (NIPS 2021) [Paper][Github]
• BEVDet: High-Performance Multi-Camera 3D Object Detection in Bird-Eye-View (Arxiv 2022) [Paper] [Github]
• DETR3D：3D Object Detection from Multi-view Image via 3D-to-2D Queries (CORL 2021) [Paper] [Github]
• BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework (NeurIPS 2022) [Paper][Github]
• Unifying Voxel-based Representation withTransformer for 3D Object Detectio (NeurIPS 2022) [paper][Github]
• Polar Parametrization for Vision-based Surround-View 3D Detection (arxiv 2022) [Paper] [Github]
• SRCN3D: Sparse R-CNN 3D Surround-View Camera Object Detection and Tracking for Autonomous Driving (Arxiv 2022) [Paper] [Github]
• BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection (Arxuv 2022) [Paper] [Github]
• BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stere (Arxiv 2022) [Paper][Github]
• MV-FCOS3D++: Multi-View Camera-Only 4D Object Detection with Pretrained Monocular Backbones (Arxiv 2022) [Paper] [Github]
• Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object （Arxiv 2022）[Paper]
• DETR4D: Direct Multi-View 3D Object Detection with Sparse Attention (Arxiv 2022) [Paper]
• Multi-Camera Calibration Free BEV Representation for 3D Object Detection (Arxiv 2022) [Paper]
• SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detectio (IROS 2023) [Paper]
• BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks (Arxiv 2022) [Paper]
• STS: Surround-view Temporal Stereo for Multi-view 3D Detection (Arxiv 2022) [Paper]
• BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object Detection (Arxiv 2022) [Paper]
• Multi-Camera Calibration Free BEV Representation for 3D Object Detection (Arxiv 2022) [Paper]
• AutoAlign: Pixel-Instance Feature Aggregationfor Multi-Modal 3D Object Detection (IJCAI 2022) [Paper]
• Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection (ACM MM 2022) [paper][Github]
• ORA3D: Overlap Region Aware Multi-view 3D Object Detection (BMVC 2022) [Paper] [Project Page]
• AutoAlignV2: Deformable Feature Aggregation for DynamicMulti-Modal 3D Object Detection (ECCV 2022) [Paper][Github]
• CenterFormer: Center-based Transformer for 3D Object Detection (ECCV 2022) [paper][Github]
• SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention (ECCV 2022) [Paper][Github]
• Position Embedding Transformation for Multi-View 3D Object Detection (ECCV 2022) [Paper] [Github]
• BEVDepth: Acquisition of Reliable Depth forMulti-view 3D Object Detection (AAAI 2023) [Paper] [Github]
• PolarFormer: Multi-camera 3D Object Detectionwith Polar Transformers (AAAI 2023) [Paper][Github]
• A Simple Baseline for Multi-Camera 3D Object Detection (AAAI 2023) [Paper][Github]
• Cross Modal Transformer via Coordinates Encoding for 3D Object Dectection (Arxiv 2023) [Paper] [Github]
• Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion (Arxiv 2023) [Paper] [Github]
• BEVSimDet: Simulated Multi-modal Distillation in Bird's-Eye View for Multi-view 3D Object Detection (Arxiv 2023) [Paper][Github]
• BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo (Arxiv 2023) [Paper]
• BSH-Det3D: Improving 3D Object Detection with BEV Shape Heatmap (Arxiv 2023) [Paper] [Github]
• DORT: Modeling Dynamic Objects in Recurrent for Multi-Camera 3D Object Detection and Tracking (Arxiv 2023) [Paper] [Github]
• Geometric-aware Pretraining for Vision-centric 3D Object Detection (Arxiv 2023) [Paper] [Github]
• Exploring Recurrent Long-term Temporal Fusion for Multi-view 3D Perception (Arxiv 2023) [Paper]
• OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection (Arxiv 2023) [Paper]
• Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction (ICCV 2023) [Paper] [Github]
• VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection (Arxiv 2023) [Paper]
• Object as Query: Equipping Any 2D Object Detector with 3D Detection Ability (Arxiv 2023) [Paper]
• VoxelFormer: Bird’s-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection (Arxiv 2023) [Paper] [Github]
• TiG-BEV: Multi-view BEV 3D Object Detection via Target Inner-Geometry Learning (Arxiv 2023) [Paper] [Github]
• CrossDTR: Cross-view and Depth-guided Transformersfor 3D Object Detection (ICRA 2023) [Paper][Github]
• SOLOFusion: Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection (ICLR 2023) [paper][Github]
• BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection (ICLR 2023) [Paper][Github]
• UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View (CVPR 2023)[Paper][Github]
• Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving (CVPR 2023) [Paper]
• Uni3D: A Unified Baseline for Multi-dataset 3D Object Detection (CVPR 2023) [Paper] [Github]
• Aedet: Azimuth-invariant multi-view 3d object detection (CVPR 2023) [Paper] [Github] [Project]
• BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection (CVPR 2023) [Paper] [Github]
• CAPE: Camera View Position Embedding for Multi-View 3D Object Detection (CVPR 2023) [Paper] [Github]
• FrustumFormer: Adaptive Instance-aware Resampling for Multi-view 3D Detection (CVPR 2023) [Paper] [Github]
• Sparse4D v2 Recurrent Temporal Fusion with Sparse Model （Arxiv 2023） [Paper] [Github]
• DA-BEV : Depth Aware BEV Transformer for 3D Object Detection (Arxiv 2023) [Paper]
• BEV-IO: Enhancing Bird’s-Eye-View 3D Detectionwith Instance Occupancy (Arxiv 2023) [Paper]
• OCBEV: Object-Centric BEV Transformer for Multi-View 3D Object Detection (Arxiv) [Paper]
• SA-BEV: Generating Semantic-Aware Bird’s-Eye-View Feature for Multi-view 3D Object Detection (ICCV 2023) [Paper] [Github]
• Predict to Detect: Prediction-guided 3D Object Detection using Sequential Images (Arxiv 2023) [paper]
• DFA3D: 3D Deformable Attention For 2D-to-3D Feature Lifting (Arxiv 2023) [Paper]
• Far3D: Expanding the Horizon for Surround-view 3D Object Detection (Arxiv 2023) [Paper]
• HeightFormer: Explicit Height Modeling without Extra Data for Camera-only 3D Object Detection in Bird’s Eye View (Arxiv 2023) [paper]
• Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection (ICCV 2023) [Paper] [Github]
• 3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection Transformers (ICCV 2023) [Paper] [Github] [Github]
• FB-BEV: BEV Representation from Forward-Backward View Transformations (ICCV 2023) [paper] [Github]
• QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection (ICCV 2023) [Paper]
• SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos (ICCV 2023) [Paper] [Github]
• NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection (ICCV 2023) [paper] [Github]
• DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023) [paper]
• BEVHeight++: Toward Robust Visual Centric 3D Object Detection (Arxiv 2023) [paper]
• UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities (Arxiv 2023) [Paper]
• Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving (Arxiv 2023) [Paper]
• Pixel-Aligned Recurrent Queries for Multi-View 3D Object Detection (ICCV 2023) [Paper] [Github] [Project]
• CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion (Arxiv 2023) [paper]
• DynamicBEV: Leveraging Dynamic Queries and Temporal Context for 3D Object Detection (Arxiv 2023) [paper]
• TOWARDS GENERALIZABLE MULTI-CAMERA 3D OBJECT DETECTION VIA PERSPECTIVE DEBIASING (Arxiv 2023) [Paper]
• Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection (NeurIPS 2023) (Arxiv 2023) [Paper] [Github]
• M&M3D: Multi-Dataset Training and Efficient Network for Multi-view 3D Object (Arxiv 2023) [Paper]
• Sparse4D v3 Advancing End-to-End 3D Detection and Tracking (Arxiv 2023) [Paper] [Github]
• BEVNeXt: Reviving Dense BEV Frameworks for 3D Object Detection (Arxiv 2023) [paper]
• Towards Efficient 3D Object Detection in Bird’s-Eye-View Space for Autonomous Driving: A Convolutional-Only Approach [Paper]
• Residual Graph Convolutional Network for Bird”s-Eye-View Semantic Segmentation (Arxiv 2023) [Paper]
• Diffusion-Based Particle-DETR for BEV Perception (Arxiv 2023) [paper]
• M-BEV: Masked BEV Perception for Robust Autonomous Driving (Arxiv 2023) [Paper]
• Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps (Arxiv 2023) [Paper]
• Sparse Dense Fusion for 3D Object Detection (Arxiv 2023) [Paper]
• WidthFormer: Toward Efficient Transformer-based BEV View Transformation (Arxiv 2023) [Paper] [Github]
• UniVision: A Unified Framework for Vision-Centric 3D Perception (Arxiv 2024) [Paper]
• DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception (Arxiv 2024) [Paper]
• Towards Scenario Generalization for Vision-based Roadside 3D Object Detection (Arxiv 2024) [Paper] [Github]

• PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images (Axxiv 2023) [Paper] [Github]
• X-Align: Cross-Modal Cross-View Alignment for Bird’s-Eye-View Segmentation (WACV 2023) [Paper]
• BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation (ICRA 2023) [Paper] [Github] [Project] UniM2AE: Multi-modal Masked Autoencoders with Unified 3D Representation for 3D Perception in Autonomous Driving (Arxiv 2023) [Paper]
• BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation (Arxiv 2023) [paper]
• Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding (Arxiv 2023) [paper]
• LiDAR2Map: In Defense of LiDAR-Based Semantic Map Construction Using Online Camera Distillation (CVPR 2023) [Paper] [Github]
• BEV-Guided Multi-Modality Fusion for Driving Perception (CVPR 2023) [Paper] [Github]
• FUSIONFORMER: A MULTI-SENSORY FUSION IN BIRD’S-EYE-VIEW AND TEMPORAL CONSISTENT TRANSFORMER FOR 3D OBJECTION (Arxiv 2023) [paper]
• UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation (ICCV 2023) [Paper] [Github]
• BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird’s Eye View Map Construction (Arxiv 2023) [Paper]

• LidarMultiNet: Unifying LiDAR Semantic Segmentation, 3D Object Detection, and Panoptic Segmentation in a Single Multi-task Network (Arxiv 2022) [paper]
• SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation (Arxiv 2023) [Paper]
• BEVContrast: Self-Supervision in BEV Space for Automotive Lidar Point Clouds (3DV 2023) [Paper] [Github]

• Learning to Look around Objects for Top-View Representations of Outdoor Scenes (ECCV 2018) [paper]
• A Parametric Top-View Representation of Complex Road Scenes (CVPR 2019) [Paper]
• Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networks (ICRA 2019 IEEE RA-L 2019) [Paper] [Github]
• Short-Term Prediction and Multi-Camera Fusion on Semantic Grids (ICCVW 2019) [paper]
• Predicting Semantic Map Representations from Images using Pyramid Occupancy Networks (CVPR 2020) [Paper] [Github]
• MonoLayout : Amodal scene layout from a single image (WACV 2020) [Paper] [Github]
• Bird’s Eye View Segmentation Using Lifted2D Semantic Features (BMVC 2021) [Paper]
• Enabling Spatio-temporal aggregation in Birds-Eye-View Vehicle Estimation (ICRA 2021) [Paper] [mp4]
• Projecting Your View Attentively: Monocular Road Scene Layout Estimation viaCross-view Transformation (CVPR 2021) [Paper] [Github]
• ViT BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation (IEEE IJCNN 2022) [paper]
• Bird's-Eye-View Panoptic Segmentation Using Monocular Frontal View Images (IEEE RA-L 2022) [Paper] [Github] [Project]
• Understanding Bird's-Eye View of Road Semantics using an Onboard Camera (ICRA 2022) [Paper] [Github]
• “The Pedestrian next to the Lamppost”Adaptive Object Graphs for Better Instantaneous Mapping (CVPR 2022) [Paper]
• Weakly But Deeply Supervised Occlusion-Reasoned Parametric Road Layouts (CVPR 2022) [Paper]
• Translating Images into Maps (ICRA 2022) [Paper] [Github]
• GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation (ECCV 2022) [Paper]
• SBEVNet: End-to-End Deep Stereo Layout Estimation (WACV 2022) [Paper]
• BEVSegFormer: Bird’s Eye View Semantic Segmentation From ArbitraryCamera Rigs (WACV 2023) [Paper]
• DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception (Arxiv 2023) [Paper] [Github]
• HFT: Lifting Perspective Representations via Hybrid Feature Transformation (ICRA 2023) [Paper] [Github]
• SkyEye: Self-Supervised Bird's-Eye-View Semantic Mapping Using Monocular Frontal View Images (Arxiv 2023) [Paper]
• Calibration-free BEV Representation for Infrastructure Perception (Arxiv 2023) [Paper]
• Semi-Supervised Learning for Visual Bird’s Eye View Semantic Segmentation (Arxiv 2023) [Paper]
• DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEVPerception (Arxiv 2023) [paper] [github] [Project]
• CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity (Arxiv 2023) [Paper]

• 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 （IEEE ITSC 2020）[Paper] [Github]
• Cross-view Semantic Segmentation for Sensing Surroundings (IROS 2020 IEEE RA-L 2020) [Paper] [Github] [Project]
• Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020) [Paper] [Github] [Project]
• Cross-view Transformers for real-time Map-view Semantic Segmentation (CVPR 2022) [Paper] [Github]
• Scene Representation in Bird’s-Eye View from Surrounding Cameras withTransformers (CVPRW 2022) [Paper]
• M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation (Arxiv 2022) [Paper] [Project]
• BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving (Arxiv 2022) [Paper] [Github]
• Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer (Arxiv 2022) [Paper] [Github]
• A Simple Baseline for BEV Perception Without LiDAR (Arxiv 2022) [Paper] [Github] [Project Page]
• UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View (ICCV 2023) [Paper] [Github
• LaRa: Latents and Rays for Multi-CameraBird’s-Eye-View Semantic Segmentation (CORL 2022) [Paper]) [Github]
• CoBEVT: Cooperative Bird’s Eye View Semantic Segmentation with Sparse Transformers (CORL 2022) [Paper] [Github]
• Vision-based Uneven BEV Representation Learningwith Polar Rasterization and Surface Estimation (CORL 2022) [Paper] [Github]
• BEVFormer: a Cutting-edge Baseline for Camera-based Detection (ECCV 2022) [Paper] [Github]
• JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in Driving Scenes (ECCV 2022) [Paper] [Github]
• Learning Ego 3D Representation as Ray Tracing (ECCV 2022) [Paper] [Github]
• Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception (NIPS 2022 Workshop) [Paper] or [Paper] [Github]
• Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline (Arxiv 2023) [Paper] [Github]
• BEVFormer v2: Adapting Modern Image Backbones toBird’s-Eye-View Recognition via Perspective Supervision (CVPR 2023) [Paper]
• MapPrior: Bird’s-Eye View Map Layout Estimation with Generative Models (CVPR 2023) [Paper]
• Bi-Mapper: Holistic BEV Semantic Mapping for Autonomous Driving (Arxiv 2023) [paper] [Github]
• MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception (ICCV 2023) [Paper] [Github]
• MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation (ICCV 2023) [paper] [Github] [Project]
• One Training for Multiple Deployments: Polar-based Adaptive BEV Perception for Autonomous Driving (Arxiv 2023) [Paper]
• RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions (Arxiv 2023) [paper] [Github] [Project]
• X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation (Arxiv 2023) [Paper]
• PowerBEV: A Powerful Yet Lightweight Framework forInstance Prediction in Bird’s-Eye View (Axriv 2023) [paper]
• Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird’s-Eye View (ICCV 2023) [Paper]
• Towards Viewpoint Robustness in Bird’s Eye View Segmentation (ICCV 2023) [Paper] [Project]
• PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird’s-Eye View (Arxiv 2023) [Paper]
• PointBeV: A Sparse Approach to BeV Predictions (Arxiv 2023) [paper] [Github]
• DualBEV: CNN is All You Need in View Transformation (Arxiv 2024) [Paper]

• Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning (WACV 2021) [Paper]
• HOPE: Hierarchical Spatial-temporal Network for Occupancy Flow Prediction (CVPRW 2022) [paper]

• FIERY: Future Instance Prediction in Bird’s-Eye View from Surround Monocular Cameras (ICCV 2021) [Paper] [Github] [Project]
• NEAT: Neural Attention Fields for End-to-End Autonomous Driving (ICCV 2021) [Paper] [Github]
• ST-P3: End-to-end Vision-based AutonomousDriving via Spatial-Temporal Feature Learning (ECCV 2022) [Paper] [Github]
• StretchBEV: Stretching Future InstancePrediction Spatially and Temporally (ECCV 2022) [Paper] [Github] [Projet]
• TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving (CVPR 2023) [Paper] [Github]
• Planning-oriented Autonomous Driving (CVPR 2023, Occupancy Prediction) [paper] [Github] [Project]
• Think Twice before Driving:Towards Scalable Decoders for End-to-End Autonomous Driving (CVPR 2023) [Paper] [Github]
• ReasonNet: End-to-End Driving with Temporal and Global Reasoning (CVPR 2023) [Paper]
• LiDAR-BEVMTN: Real-Time LiDAR Bird’s-Eye View Multi-Task Perception Network for Autonomous Driving (Arxiv 2023) [paper]
• FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving (Arxiv 2023) [Paper]
• VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning (Arxiv 2024) [Paper] [Project]https://hgao-cv.github.io/VADv2/

• Hierarchical Recurrent Attention Networks for Structured Online Map (CVPR 2018) [Paper]

• End-to-End Deep Structured Models for Drawing Crosswalks (ECCV 2018) [Paper]
• Probabilistic Semantic Mapping for Urban Autonomous Driving Applications (IROS 2020) [Paper] [Github]
• Convolutional Recurrent Network for Road Boundary Extraction (CVPR 2022) [Paper]
• Lane Graph Estimation for Scene Understanding in Urban Driving (IEEE RAL 2021) [Paper]
• M^2-3DLaneNet: Multi-Modal 3D Lane Detection (Arxiv 2022) [paper] [Github]
• HDMapNet: An Online HD Map Construction and Evaluation Framework (ICRA 2022) [paper] [Github] [Project]
• SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation (Arxiv 2023) [paper] [Github]
• VMA: Divide-and-Conquer Vectorized MapAnnotation System for Large-Scale Driving Scene (Arxiv 2023) [Paper]
• THMA: Tencent HD Map AI System for Creating HD Map Annotations (AAAI 2023) [paper]

• RoadTracer: Automatic Extraction of Road Networks from Aerial Images (CVPR 2018) [Paper] [Github]
• DAGMapper: Learning to Map by Discovering Lane Topology (ICCV 2019) [paper]
• End-to-end Lane Detection through Differentiable Least-Squares Fitting (ICCVW 2019) [paper]
• VecRoad: Point-based Iterative Graph Exploration for Road Graphs Extraction (CVPR 2020) [Paper] [Github] [Project]
• Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding (ECCV 2020) [paper] [Github]
• iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous Driving (ICRA 2021 IEEE RA-L) [paper] [Github] [Project]
• HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps (CVPR 2021) [paper]
• Structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images (ICCV 2021) [Paper] [Github]
• RNGDet: Road Network Graph Detection by Transformer in Aerial Images (IEEE TGRS 2022) [[Paper] [Project]
• RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement (IEEE RA-L 2022) [Paper] [Github] [Project]
• SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving (ICRA 2022) [paper] [Github]
• Laneformer: Object-aware Row-Column Transformers for Lane Detection (AAAI 2022) [Paper]
• Lane-Level Street Map Extraction from Aerial Imagery (WACV 2022) [Paper] [Github]
• Reconstruct from Top View: A 3D Lane Detection Approach based on GeometryStructure Prior (CVPRW 2022) [paper]
• PolyWorld: Polygonal Building Extraction with Graph Neural Networks in Satellite Images (CVPR 2022) [Paper] [Github]
• Topology Preserving Local Road Network Estimation from Single Onboard Camera Image (CVPR 2022) [Paper] [Github]
• TD-Road: Top-Down Road Network Extraction with Holistic Graph Construction (ECCV 2022) [Paper]
• CLiNet: Joint Detection of Road Network Centerlines in 2D and 3D (IEEE IVS 2023) [Paper]
• Polygonizer: An auto-regressive building delineator (ICLRW 2023) [Paper]
• CurveFormer: 3D Lane Detection by Curve Propagation with CurveQueries and Attention (ICRA 2023) [Paper]
• Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection (CVPR 2023) [paper] [Github]
• Learning and Aggregating Lane Graphs for Urban Automated Driving (Arxiv 2023) [paper]
• Online Lane Graph Extraction from Onboard Video (Arxiv 2023) [paper] [Github]
• Video Killed the HD-Map: Predicting Driving BehaviorDirectly From Drone Images (Arxiv 2023) [Paper]
• Prior Based Online Lane Graph Extraction from Single Onboard Camera Image (Arxiv 2023) [Paper]
• Online Monocular Lane Mapping Using Catmull-Rom Spline (Arxiv 2023) [Paper] [Github]
• Improving Online Lane Graph Extraction by Object-Lane Clustering (ICCV 2023) [Paper]
• LATR: 3D Lane Detection from Monocular Images with Transformer (ICCV 2023) [Paper] [Github]
• Patched Line Segment Learning for Vector Road Mapping (Arxiv 2023) [paper]
• Sparse Point Guided 3D Lane Detection (ICCV 2023) [Paper] [Github]
• Recursive Video Lane Detection (ICCV 2023) [Paper] [Github]
• LATR: 3D Lane Detection from Monocular Images with Transformer (ICCV 2023) [Paper] [Github]
• Occlusion-Aware 2D and 3D Centerline Detection for Urban Driving via Automatic Label Generation (ARXIV 2023) [PAPER]
• BUILDING LANE-LEVEL MAPS FROM AERIAL IMAGES (Arxiv 2023) [paper]

• PersFormer: a New Baseline for 3D Laneline Detection (ECCV 2022) [Paper] [Github]
• Continuity-preserving Path-wise Modeling for Online Lane Graph Construction (Arxiv 2023) [paper] [Github]
• VAD: Vectorized Scene Representation for Efficient Autonomous Driving (Arxiv 2023) [paper] [Github]
• InstaGraM: Instance-level Graph Modelingfor Vectorized HD Map Learning (Arxiv 2023) [Paper]
• VectorMapNet: End-to-end Vectorized HD Map Learning (Arxiv 2023) [Paper] [Github] [Project]
• Road Genome: A Topology Reasoning Benchmark for Scene Understanding in Autonomous Driving (Arxiv 2023) [Paper] [Github]
• Topology Reasoning for Driving Scenes (Arxiv 2023) [paper] [Github]
• MV-Map: Offboard HD-Map Generation with Multi-view Consistency （Arxiv 2023） [paper] [Github]
• CenterLineDet: Road Lane CenterLine Graph Detection With Vehicle-Mounted Sensors by Transformer for High-definition Map Creation (ICRA 2023) [paper] [Github]
• Structured Modeling and Learning for Online Vectorized HD Map Construction (ICLR 2023) [paper] [Github]
• Neural Map Prior for Autonomous Driving (CVPR 2023) [Paper]
• An Efficient Transformer for Simultaneous Learning of BEV and LaneRepresentations in 3D Lane Detection (Arxiv 2023) [paper]
• TopoMask: Instance-Mask-Based Formulation for the Road Topology Problemvia Transformer-Based Architecture (Arxiv 2023) [apper]
• PolyDiffuse: Polygonal Shape Reconstruction viaGuided Set Diffusion Models (Arxiv 2023) [paper] [Github] [Project]
• Online Map Vectorization for Autonomous Driving: A Rasterization Perspective (Arxiv 2023) [Paper]
• NeMO: Neural Map Growing System forSpatiotemporal Fusion in Bird’s-Eye-Viewand BDD-Map Benchmark (Arxiv 2023) [Paper]
• MachMap: End-to-End Vectorized Solution for Compact HD-Map Construction (CVPR 2023 Workshop) [Paper]
• Lane Graph as Path: Continuity-preserving Path-wise Modelingfor Online Lane Graph Construction (Arxiv 2023) [paper]
• End-to-End Vectorized HD-map Construction with Piecewise B ́ezier Curve (CVPR 2023) [Paper] [Github]
• GroupLane: End-to-End 3D Lane Detection with Channel-wise Grouping (Arxiv 2023) [Paper]
• MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction (Arxiv 2023) [Paper]
• LATR: 3D Lane Detection from Monocular Images with Transformer (Arxiv 2023) [Paper]
• INSIGHTMAPPER: A CLOSER LOOK AT INNER-INSTANCE INFORMATION FOR VECTORIZED HIGH-DEFINITION MAPPING (Arxiv 2023) [Paper] [Project] [Github]
• HD Map Generation from Noisy Multi-Route Vehicle Fleet Data on Highways with Expectation Maximization (Arxiv 2023) [Paper]
• StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Construction (WACV 2024) [Paper] [Github]
• PivotNet: Vectorized Pivot Learning for End-to-end HD Map Construction (ICCV 2023) [Paper]
• Translating Images to Road Network: A Non-Autoregressive Sequence-to-Sequence Approach (ICCV 2023) [paper]
• TopoMLP: An Simple yet Strong Pipeline for Driving Topology Reasoning (Arxiv 2023) [paper] [Github]
• ScalableMap: Scalable Map Learning for Online Long-Range Vectorized HD Map Construction (CoRL 2023) [Paper] [Github]
• Mind the map! Accounting for existing map information when estimating online HDMaps from sensor data (Arxiv 2023) [Paper]
• Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps (Arxiv 2023) [Paper]
• P-MAPNET: FAR-SEEING MAP CONSTRUCTOR ENHANCED BY BOTH SDMAP AND HDMAP PRIORS (ICLR 2024 submitted paper) [Openreview] [Paper]
• Online Vectorized HD Map Construction using Geometry (Arxiv 2023) [paper] [Github]
• LANESEGNET: MAP LEARNING WITH LANE SEGMENT PERCEPTION FOR AUTONOMOUS DRIVING (Arxiv 2023) [paper] [Github]
• 3D Lane Detection from Front or Surround-View using Joint-Modeling & Matching (Arxiv 2024) [Paper
• MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction (Arxiv 2024) [Paper]
• Stream Query Denoising for Vectorized HD Map Construction (Arxiv 2024) [Paper]
• ADMap: Anti-disturbance framework for reconstructing online vectorized HD map (Arxiv 2024) [Paper]
• PLCNet: Patch-wise Lane Correction Network for Automatic Lane Correction in High-definition Maps (Arxiv 2024) [Paper]
• LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement (AAAI 2024) [paper]
• VI-Map: Infrastructure-Assisted Real-Time HD Mapping for Autonomous Driving (Arxiv 2024) [Paper]
• CurveFormer++: 3D Lane Detection by Curve Propagation with Temporal Curve Queries and Attention (Arxiv 2024) [Paper]
• VI-Map: Infrastructure-Assisted Real-Time HD Mapping for Autonomous Driving (Arxiv 2024) [paper]
• Lane2Seq: Towards Unified Lane Detection via Sequence Generation (CVPR 2024) [Paper]
• Leveraging Enhanced Queries of Point Sets for Vectorized Map Construction (Arxiv 2024) [Paper]

• Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer (Arxiv 2022) [Paper] [Github]
• EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View (Arxiv 2023) [paper] [Github]

• BEV-Locator: An End-to-end Visual Semantic Localization Network Using Multi-View Images (Arxiv 2022) [paper]
• BEV-SLAM: Building a Globally-Consistent WorldMap Using Monocular Vision (IROS 2022) [Paper]
• U-BEV: Height-aware Bird’s-Eye-View Segmentation and Neural Map-based Relocalization (Arxiv 2023) [Paper]

• Occupancy Networks: Learning 3D Reconstruction in Function Space (CVPR 2019) [Paper] [Github]
• 3D Semantic Scene Completion: a Survey (IJCV 2021) [Paper]
• Estimation of Appearance and Occupancy Information in Bird’s EyeView from Surround Monocular Images (Arxiv 2022) [paper] [Project]
• Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds (IROS 2021) [Paper] [Github]
• Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review (Arxiv 2023) [paper]
• LMSCNet: Lightweight Multiscale 3D Semantic Completion (IC 3DV 2020) [Paper] [[Github]
• MonoScene: Monocular 3D Semantic Scene Completion (CVPR 2022) [Paper] [Github] [Project]
• OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction (ICCV 2023) [Paper] [Github]
• A Simple Attempt for 3D Occupancy Estimation in Autonomous Driving (Arxiv 2023) [Paper] [Github]
• OccDepth: A Depth-aware Method for 3D Semantic Occupancy Network (Arxiv 2023) [Paper] [Github]
• OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception (Arxiv 2023) [paper] [Github]
• Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving (Arxiv 2023) [Paper] [Github] [Project]
• Occ-BEV: Multi-Camera Unified Pre-training via 3DScene Reconstruction (Arxiv 2023) [Paper] [Github]
• StereoScene: BEV-Assisted Stereo Matching Empowers 3D Semantic Scene Completion (Arxiv 2023) [paper] [Github]
• Learning Occupancy for Monocular 3D Object Detection (Arxiv 2023) [Paper] [Github]
• OVO: Open-Vocabulary Occupancy (Arxiv 2023) [Paper]
• SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving (Arxiv 2023) [paper] [Github] [Project]
• Scene as Occupancy (Arxiv 2023) [[Paper]]](https://arxiv.org/pdf/2306.02851.pdf) [Github]
• Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data (Arxiv 2023) [Paper] [Github]
• PanoOcc: Unified Occupancy Representation for Camera-based3D Panoptic Segmentation (Arxiv 2023) [Paper] [Github]
• UniOcc: Unifying Vision-Centric 3D Occupancy Predictionwith Geometric and Semantic Rendering (Arxiv 2023) [paper]
• SSCBench: A Large-Scale 3D Semantic Scene Completion Benchmark for Autonomous Driving (NeurIPS 2023 D&B track) [paper] [paper]
• StereoVoxelNet: Real-Time Obstacle Detection Based on OccupancyVoxels from a Stereo Camera Using Deep Neural Networks (ICRA 2023) [[Paper]] (https://arxiv.org/pdf/2209.08459.pdf) [Github] [Project]
• Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction (CVPR 2023) [Paper] [Github]
• VoxFormer: a Cutting-edge Baseline for 3D Semantic Occupancy Prediction (CVPR 2023) [paper] [Github]
• Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting (CVPR 2023) [Paper] [Github] [Project]
• SSCBench: A Large-Scale 3D Semantic SceneCompletion Benchmark for Autonomous Driving (Arxiv 2023) [paper] [Github]
• SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion (IROS 2023) [Paper] [Github]
• CVSformer: Cross-View Synthesis Transformer for Semantic Scene Completion (Arxiv 2023) [paper]
• Symphonize 3D Semantic Scene Completion with Contextual Instance Queries (Arxiv 2023) [Paper] [Github]
• Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders (Arxiv 2023) [paper]
• UniWorld: Autonomous Driving Pre-training via World Models (Arxiv 2023) [Paper] [Github]
• PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction (Arxiv 2023) [paper] [Github]
• SOGDet: Semantic-Occupancy Guided Multi-view 3D Object Detection (Arxiv 2023) [paper] [Github]
• OccupancyDETR: Making Semantic Scene Completion as Straightforward as Object Detection (Arxiv 2023) [Paper] [Github]
• PointSSC: A Cooperative Vehicle-Infrastructure Point Cloud Benchmark for Semantic Scene Completion (Arxiv 2023) [Paper]
• SPOT: SCALABLE 3D PRE-TRAINING VIA OCCUPANCY PREDICTION FOR AUTONOMOUS DRIVING (Arxiv 2023) [paper]
• NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space (Arxiv 2023) [Github]
• Anisotropic Convolutional Networks for 3D Semantic Scene Completion (CVPR 2020) [Github] [Project]
• RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervision (Arxiv 2023) [paper] [Github]
• LiDAR-based 4D Occupancy Completion and Forecasting (Arxiv 2023) [Paper] [Github]
• SOccDPT: Semi-Supervised 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints (Arxiv 2023) [Paper]
• SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction (Arxiv 2023) [Paper] [Github]
• FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin (Arxiv 2023) [paper]
• Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications (Arxiv 2023) [paper] [Github]
• OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving (Arxiv 2023) [paper] [Github]
• DepthSSC: Depth-Spatial Alignment and Dynamic Voxel Resolution for Monocular 3D Semantic Scene Completion (Arxiv 2023) [Paper]
• A Simple Framework for 3D Occupancy Estimation in Autonomous Driving (Arxiv 2023) [Paper] [Github]
• OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries (Arxiv 2023) [Paper]
• COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction (Arxiv 2023) [Paper]
• OccNeRF: Self-Supervised Multi-Camera Occupancy Prediction with Neural Radiance Fields (Arxiv 2023) [paper] [Github]
• RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation (Arxiv 2023) [paper]
• PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness (Arxiv 2023) [paper] [Project] [Github]
• POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images (Arxiv 2024) [Paper] [Github]
• S2TPVFormer: Spatio-Temporal Tri-Perspective View for temporally coherent 3D Semantic Occupancy Prediction (Arxiv 2024) [Paper]
• InverseMatrixVT3D: An Efficient Projection Matrix-Based Approach for 3D Occupancy Prediction (Arxiv 2024) [Paper]
• V2VSSC: A 3D Semantic Scene Completion Benchmark for Perception with Vehicle to Vehicle Communication (Arxiv 2024) [Paper]
• OccFlowNet: Towards Self-supervised Occupancy Estimation via Differentiable Rendering and Occupancy Flow (Arxiv 2024) [Paper]
• OccFusion: A Straightforward and Effective Multi-Sensor Fusion Framework for 3D Occupancy Prediction (Arxiv 2024) [Paper]
• OccTransformer: Improving BEVFormer for 3D camera-only occupancy prediction (Arxiv 2024) [Paper]
• FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View (ICRA 2024) [Paper]
• OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction (Arxiv 2024) [paper]
• PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness (CVPR 2024) [Paper] [Github]

• FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation (CVPR 2023 3D Occupancy Prediction Challenge WorkShop) [paper] [Github]
• Separated RoadTopoFormer (Arxiv 2023) [Paper]
• OCTraN: 3D Occupancy Convolutional Transformer Network in Unstructured Traffic Scenarios (CVPR 2023 WorkShop) [Paper] [Github]

• The 1st-place Solution for CVPR 2023 OpenLane Topologyin Autonomous Driving Challenge [Paper]

• Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark (CVPR 2023) [paper] [Github]

• Talk2BEV: Language-enhanced Bird’s-eye View Maps for Autonomous Driving (ICRA 2024) [paper] [Github] [Project]
• MotionLM: Multi-Agent Motion Forecasting as Language Modeling (Arxiv 2023) [paper]
• GAIA-1: A Generative World Model for Autonomous Driving (Arxiv 2023) [paper]
• DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving (Arxiv 2023) [paper]
• Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving (Arxiv 2023) [Paper] [Github]
• Learning to Drive Anywhere (CORL 2023) [Paper]
• Language-Conditioned Path Planning (Arxiv 2023) [paper]
• DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model (Arxiv 2023) [Paper] [Project]
• GPT-Driver: Learning to Drive with GPT (Arxiv 2023) [Paper]
• LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving (Arxiv 2023) [paper]
• TOWARDS END-TO-END EMBODIED DECISION MAKING VIA MULTI-MODAL LARGE LANGUAGE MODEL: EXPLORATIONS WITH GPT4-VISION AND BEYOND (Arxiv 2023) [Paper]
• DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model (Arxiv 2023) [Paper]
• UNIPAD: A UNIVERSAL PRE-TRAINING PARADIGM FOR AUTONOMOUS DRIVING (Arxiv 2023) [paper] [Github]
• PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm (Arxiv 2023) [Paper]
• Uni3D: Exploring Unified 3D Representation at Scale (Arxiv 2023) [Paper] [Github]
• Video Language Planning (Arxiv 2023) [paper] [Github]
• RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models (Arxiv 2023) [Paper]
• DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning (Arxiv 2023) [Paper] [Paper] [Project]
• Vision Language Models in Autonomous Driving and Intelligent Transportation Systems (Arxiv 2023) [Paper]
• ADAPT: Action-aware Driving Caption Transformer (ICRA 2023) [Paper] [Github]
• Language Prompt for Autonomous Driving (Arxiv 2023) [paper] [Github]
• Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models (Arxiv 2023) [Paper] [Project]
• LEARNING UNSUPERVISED WORLD MODELS FOR AUTONOMOUS DRIVING VIA DISCRETE DIFFUSION (Arxiv 2023) [Paper]
• ADriver-I: A General World Model for Autonomous Driving (Arxiv 2023) [Paper]
• HiLM-D: Towards High-Resolution Understanding in Multimodal Large Language Models for Autonomous Driving (Arxiv 2023) [Paper]
• On the Road with GPT-4V(vision): Early Explorations of Visual-Language Model on Autonomous Driving (Arxiv 2023) [paper]
• GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning (Arxiv 2023) [Paper]
• Applications of Large Scale Foundation Models for Autonomous Driving (Arxiv 2023) [Paper]
• Dolphins: Multimodal Language Model for Driving (Arxiv 2023) [Paper] [Project]
• Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving (Arxiv 2023) [paper] [Github] [Project]
• Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving? (Arxiv 2023) [Paper] [Github]
• NuScenes-MQA: Integrated Evaluation of Captions and QA for Autonomous Driving Datasets using Markup Annotations (Arxiv 2023) [paper] [Github]
• DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving (Arxiv 2023) [Paper] [[Github]
• DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes (Arxiv 2023) [Paper] [Project]
• Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving (Arxiv 2023) [Paper] [Github]
• Dialogue-based generation of self-driving simulation scenarios using Large Language Models (Arxiv 2023) [Paper] [Github]
• Panacea: Panoramic and Controllable Video Generation for Autonomous Driving (Arxiv 2023) [paper] [Project] [Github]
• LingoQA: Video Question Answering for Autonomous Driving (Arxiv 2023) [paper] [Github]
• DriveLM: Driving with Graph Visual Question Answering (Arxiv 2023) [Paper] [Github]
• LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding (Arxiv 2023) [Paper] [Project]
• LMDrive: Closed-Loop End-to-End Driving with Large Language Models (Arxiv 2023) [Paper] [Github]
• Visual Point Cloud Forecasting enables Scalable Autonomous Driving (Arxiv 2023) [Paper] [Github]
• WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation (Arxiv 2023) [Paper] [Github]
• Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models (Arxiv 2024) [Paper] [Github]
• DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving (Arxiv 2024) [Paper]
• A Survey on Multimodal Large Language Models for Autonomous Driving (WACVW 2024) [Paper]
• VLP: Vision Language Planning for Autonomous Driving (Arxiv 2023) [Paper]
• Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities (Arxiv 2024) [Paper]
• MapGPT: Map-Guided Prompting for Unified Vision-and-Language Navigation (Arxiv 2024) [Paper]
• Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents (Arxiv 2024) [Paper]
• DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models (Arxiv 2024) [Paper] [Github]
• GenAD: Generative End-to-End Autonomous Driving (Arxiv 2024) [Paper] [Github]

• Semantic MapNet: Building Allocentric Semantic Maps and Representations from Egocentric Views (AAAI 2021) [Paper] [Github] [Project]
• Trans4Map: Revisiting Holistic Bird’s-Eye-View Mapping from EgocentricImages to Allocentric Semantics with Vision Transformers (WACV 2023) [[Paper]](Trans4Map: Revisiting Holistic Bird’s-Eye-View Mapping from EgocentricImages to Allocentric Semantics with Vision Transformers)
• ViewBirdiformer: Learning to recover ground-plane crowd trajectories and ego-motion from a single ego-centric view (Arxiv 2022) [paper]
• 360BEV: Panoramic Semantic Mapping for Indoor Bird's-Eye View (Arxiv 2023) [Paper] [Github] [Project]
• F2BEV: Bird's Eye View Generation from Surround-View Fisheye Camera Images for Automated Driving (Arxiv 2023) [Paper]
• NVAutoNet: Fast and Accurate 360∘ 3D Visual Perception For Self Driving (Arxiv 2023) [Paper]
• FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems (Arxiv 2023) [Paper]
• Aligning Bird-Eye View Representation of PointCloud Sequences using Scene Flow (IEEE IV 2023) [Paper] [Github]
• MotionBEV: Attention-Aware Online LiDARMoving Object Segmentation with Bird’s Eye Viewbased Appearance and Motion Features (Arxiv 2023) [Paper]
• WEDGE: A multi-weather autonomous driving dataset built from generativevision-language models (Arxiv 2023) [Paper] [Github] [Project]
• Leveraging BEV Representation for360-degree Visual Place Recognition (Arxiv 2023) [Paper]
• NMR: Neural Manifold Representation for Autonomous Driving (Arxiv 2023) [Paper]
• V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer (ECCV 2022) [Paper] [Github]
• DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative3D Object Detection (CVPR 2022) [Paper] [Github]
• Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task (CVPR 2022) [Paper] [Github] [Project]
• A Motion and Accident Prediction Benchmark for V2X Autonomous Driving (Arxiv 2023) [Paper] [Project]
• BEVBert: Multimodal Map Pre-training for Language-guided Navigation (ICCV 2023) [Paper]
• V2X-Seq: A Large-Scale Sequential Dataset forVehicle-Infrastructure Cooperative Perception and Forecasting (Arxiv 2023) [Paper] [Github] [Project]
• BUOL: A Bottom-Up Framework with Occupancy-aware Lifting forPanoptic 3D Scene Reconstruction From A Single Image (CVPR 2023) [paper] [Github]
• BEVScope: Enhancing Self-Supervised Depth Estimation Leveraging Bird’s-Eye-View in Dynamic Scenarios (Arxiv 2023) [Paper]
• Bird’s-Eye-View Scene Graph for Vision-Language Navigation (Arxiv 2023) [paper]
• OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data (Arxiv 2023) [paper]
• Hidden Biases of End-to-End Driving Models (ICCV 2023) [Paper] [[Github]][https://github.com/autonomousvision/carla_garage]
• EgoVM: Achieving Precise Ego-Localization using Lightweight Vectorized Maps (Arxiv 2023) [Paper]
• End-to-end Autonomous Driving: Challenges and Frontiers (Arxiv 2023) [paper] [Github]
• BEVPlace: Learning LiDAR-based Place Recognition using Bird’s Eye View Images (ICCV 2023) [paper]
• I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird’s Eye View Projections (IROS 2023) [Paper]
• Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving (Arxiv 2023) [Paper] [Project]
• BEV-DG: Cross-Modal Learning under Bird’s-Eye View for Domain Generalization of 3D Semantic Segmentation (ICCV 2023) [paper]
• MapPrior: Bird’s-Eye View Map Layout Estimation with Generative Models (ICCV 2023) [Paper] [Github] [Project]
• Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding (ECCV 2020) [Paper] [Github]
• Occ2Net: Robust Image Matching Based on 3D Occupancy Estimation for Occluded Regions (ICCV 2023) [Paper]
• QUEST: Query Stream for Vehicle-Infrastructure Cooperative Perception (Arxiv 2023) [paper]
• Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Construction (Arxiv 2023) [Paper]
• SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping an Building Change Detection (Arxiv 2023) [paper]
• Rethinking Integration of Prediction and Planning in Deep Learning-Based Automated Driving Systems: A Review (Arxiv 2023) [Paper]
• BEV-CLIP: Multi-modal BEV Retrieval Methodology for Complex Scene in Autonomous Driving (Arxiv 2023) [paper]
• BerfScene: Bev-conditioned Equivariant Radiance Fields for Infinite 3D Scene Generation (Arxiv 2023) [Paper]
• Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception (Arxiv 2023) [paper]
• PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds (Arxiv 2023) [paper]
• BEVTrack: A Simple Baseline for 3D Single Object Tracking in Birds's-Eye-View (Arxiv 2023) [Paper] [Github]
• BEV-CV: Birds-Eye-View Transform for Cross-View Geo-Localisation (Arxiv 2023) [Paper]
• UC-NERF: NEURAL RADIANCE FIELD FOR UNDER-CALIBRATED MULTI-VIEW CAMERAS IN AUTONOMOUS DRIVING (Arxiv 2023) [paper] [Project] [Github]
• All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes (Arxiv 2023) [paper]
• BEVSeg2TP: Surround View Camera Bird’s-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction (Arxiv 2023) [Paper]
• BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout (Arxiv 2023) [Paper]
• EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI (Arxiv 2023) [Paper] [Github]
• A Vision-Centric Approach for Static Map Element Annotation (Arxiv 2023) [paper]
• C-BEV: Contrastive Bird’s Eye View Training for Cross-View Image Retrieval and 3-DoF Pose Estimation (Arxiv 2023) [paper]
• Self-Supervised Bird's Eye View Motion Prediction with Cross-Modality Signals (Arxiv 2024) [Paper]
• GeoDecoder: Empowering Multimodal Map Understanding (Arxiv 2024) [Paper]
• Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird’s-Eye-View (Arxiv 2024) [Paper]
• Text2Street: Controllable Text-to-image Generation for Street Views (Arxiv 2024) [paper]
• Zero-BEV: Zero-shot Projection of Any First-Person Modality to BEV Maps (Arxiv 2024) [Paper]
• EV2PR: BEV-Enhanced Visual Place Recognition with Structural Cues (Arxiv 2024) [paper]