{"total":193,"rows":[{"id":"2312.10035","title":"Point Transformer V3: Simpler, Faster, Stronger","created":"2023-12-15","cited_by_count":589,"area":null},{"id":"2312.09245","title":"DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving","created":"2023-12-14","cited_by_count":233,"area":"mllm"},{"id":"2203.08195","title":"DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection","created":"2022-03-15","cited_by_count":224,"area":null},{"id":"2303.11301","title":"VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking","created":"2023-03-20","cited_by_count":222,"area":null},{"id":"2303.07601","title":"V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception","created":"2023-03-14","cited_by_count":155,"area":null},{"id":"2206.09474","title":"3D Object Detection for Autonomous Driving: A Comprehensive Survey","created":"2022-06-19","cited_by_count":132,"area":null},{"id":"2208.11112","title":"DeepInteraction: 3D Object Detection via Modality Interaction","created":"2022-08-23","cited_by_count":125,"area":null},{"id":"2303.12766","title":"Spherical Transformer for LiDAR-based 3D Recognition","created":"2023-03-22","cited_by_count":125,"area":null},{"id":"2209.05324","title":"Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe","created":"2022-09-12","cited_by_count":122,"area":null},{"id":"2301.06051","title":"DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets","created":"2023-01-15","cited_by_count":122,"area":null},{"id":"2305.03045","title":"OctFormer: Octree-based Transformers for 3D Point Clouds","created":"2023-05-04","cited_by_count":109,"area":null},{"id":"2209.05588","title":"CenterFormer: Center-based Transformer for 3D Object Detection","created":"2022-09-12","cited_by_count":99,"area":null},{"id":"2210.07372","title":"SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds","created":"2022-10-13","cited_by_count":92,"area":null},{"id":"2207.10035","title":"Fully Sparse 3D Object Detection","created":"2022-07-20","cited_by_count":84,"area":null},{"id":"2303.03595","title":"LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion","created":"2023-03-07","cited_by_count":80,"area":null},{"id":"2209.09385","title":"LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perception","created":"2022-09-19","cited_by_count":74,"area":null},{"id":"2308.07732","title":"UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation","created":"2023-08-15","cited_by_count":74,"area":null},{"id":"2301.08739","title":"FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer","created":"2023-01-20","cited_by_count":73,"area":null},{"id":"2403.06467","title":"Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy","created":"2024-03-11","cited_by_count":73,"area":"ssm"},{"id":"2206.10555","title":"LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs","created":"2022-06-21","cited_by_count":72,"area":null},{"id":"2406.10700","title":"Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection","created":"2024-06-15","cited_by_count":66,"area":"ssm"},{"id":"2206.09900","title":"Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders","created":"2022-06-20","cited_by_count":58,"area":null},{"id":"2210.04264","title":"CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds","created":"2022-10-09","cited_by_count":58,"area":null},{"id":"2308.04556","title":"FocalFormer3D : Focusing on Hard Instance for 3D Object Detection","created":"2023-08-08","cited_by_count":58,"area":null},{"id":"2212.03010","title":"GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds","created":"2022-12-06","cited_by_count":57,"area":null},{"id":"2205.13764","title":"Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images","created":"2022-05-27","cited_by_count":56,"area":null},{"id":"2305.04925","title":"PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds","created":"2023-05-08","cited_by_count":54,"area":null},{"id":"2212.08273","title":"Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communication","created":"2022-12-16","cited_by_count":47,"area":null},{"id":"2403.10094","title":"RangeLDM: Fast Realistic LiDAR Point Cloud Generation","created":"2024-03-15","cited_by_count":47,"area":"wm"},{"id":"2601.00393","title":"NeoVerse: Enhancing 4D World Model with in-the-wild Monocular Videos","created":"2026-01-01","cited_by_count":46,"area":"wm"},{"id":"2310.20234","title":"HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Clouds","created":"2023-10-31","cited_by_count":45,"area":null},{"id":"2207.00531","title":"Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds","created":"2022-07-01","cited_by_count":39,"area":null},{"id":"2302.02367","title":"FastPillars: A Deployment-friendly Pillar-based 3D Detector","created":"2023-02-05","cited_by_count":39,"area":null},{"id":"2305.08808","title":"GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training","created":"2023-05-15","cited_by_count":38,"area":null},{"id":"2407.18232","title":"LION: Linear Group RNN for 3D Object Detection in Point Clouds","created":"2024-07-25","cited_by_count":38,"area":"ssm"},{"id":"2308.03755","title":"FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels","created":"2023-08-07","cited_by_count":34,"area":null},{"id":"2205.11098","title":"PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection","created":"2022-05-23","cited_by_count":33,"area":"distill"},{"id":"2212.06858","title":"LidarCLIP or: How I Learned to Talk to Point Clouds","created":"2022-12-13","cited_by_count":33,"area":null},{"id":"2311.11762","title":"MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations","created":"2023-11-20","cited_by_count":33,"area":"wm"},{"id":"2403.11848","title":"GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detection","created":"2024-03-18","cited_by_count":33,"area":null},{"id":"2301.02562","title":"Super Sparse 3D Object Detection","created":"2023-01-05","cited_by_count":32,"area":null},{"id":"2303.12621","title":"OcTr: Octree-based Transformer for 3D Object Detection","created":"2023-03-22","cited_by_count":32,"area":null},{"id":"2504.09975","title":"OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation","created":"2025-04-14","cited_by_count":30,"area":"diffusion"},{"id":"2304.12310","title":"Fully Sparse Fusion for 3D Object Detection","created":"2023-04-24","cited_by_count":29,"area":null},{"id":"2404.00469","title":"SceneGraphLoc: Cross-Modal Coarse Visual Localization on 3D Scene Graphs","created":"2024-03-30","cited_by_count":29,"area":null},{"id":"2304.12315","title":"Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection","created":"2023-04-24","cited_by_count":28,"area":null},{"id":"2306.01438","title":"Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection","created":"2023-06-02","cited_by_count":28,"area":null},{"id":"2307.07944","title":"Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling","created":"2023-07-16","cited_by_count":28,"area":null},{"id":"2207.10047","title":"Densely Constrained Depth Estimator for Monocular 3D Object Detection","created":"2022-07-20","cited_by_count":27,"area":null},{"id":"2310.05699","title":"Uni3DETR: Unified 3D Detection Transformer","created":"2023-10-09","cited_by_count":27,"area":null},{"id":"2303.13510","title":"MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training","created":"2023-03-23","cited_by_count":26,"area":null},{"id":"2311.02684","title":"Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE","created":"2023-11-05","cited_by_count":25,"area":"moe"},{"id":"2208.04309","title":"3D Vision with Transformers: A Survey","created":"2022-08-08","cited_by_count":21,"area":null},{"id":"2212.07289","title":"ConQueR: Query Contrast Voxel-DETR for 3D Object Detection","created":"2022-12-14","cited_by_count":21,"area":null},{"id":"2305.06621","title":"PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer","created":"2023-05-11","cited_by_count":21,"area":null},{"id":"2307.07313","title":"HEAL-SWIN: A Vision Transformer On The Sphere","created":"2023-07-14","cited_by_count":20,"area":null},{"id":"2311.10983","title":"Multiple View Geometry Transformers for 3D Human Pose Estimation","created":"2023-11-18","cited_by_count":19,"area":null},{"id":"2407.10749","title":"SEED: A Simple and Effective 3D DETR in Point Clouds","created":"2024-07-15","cited_by_count":19,"area":null},{"id":"2210.04801","title":"4D Unsupervised Object Discovery","created":"2022-10-10","cited_by_count":18,"area":null},{"id":"2303.13509","title":"Position-Guided Point Cloud Panoptic Segmentation Transformer","created":"2023-03-23","cited_by_count":17,"area":null},{"id":"2512.13689","title":"LitePT: Lighter Yet Stronger Point Transformer","created":"2025-12-15","cited_by_count":17,"area":null},{"id":"2312.11112","title":"ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding","created":"2023-12-18","cited_by_count":16,"area":null},{"id":"2206.04028","title":"CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving","created":"2022-06-08","cited_by_count":15,"area":null},{"id":"2303.08316","title":"MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences","created":"2023-03-15","cited_by_count":15,"area":null},{"id":"2406.08785","title":"BEVSpread: Spread Voxel Pooling for Bird's-Eye-View Representation in Vision-based Roadside 3D Object Detection","created":"2024-06-13","cited_by_count":15,"area":null},{"id":"2408.05075","title":"DeepInteraction++: Multi-Modality Interaction for Autonomous Driving","created":"2024-08-09","cited_by_count":15,"area":"driving"},{"id":"2209.10733","title":"FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection","created":"2022-09-22","cited_by_count":14,"area":null},{"id":"2306.03206","title":"MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences","created":"2023-06-05","cited_by_count":13,"area":null},{"id":"2407.11569","title":"SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds","created":"2024-07-16","cited_by_count":13,"area":null},{"id":"2304.04248","title":"Curricular Object Manipulation in LiDAR-based Object Detection","created":"2023-04-09","cited_by_count":12,"area":null},{"id":"2308.10421","title":"UniM$^2$AE: Multi-modal Masked Autoencoders with Unified 3D Representation for 3D Perception in Autonomous Driving","created":"2023-08-21","cited_by_count":12,"area":null},{"id":"2402.12535","title":"Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics","created":"2024-02-19","cited_by_count":12,"area":null},{"id":"2303.12194","title":"LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perception","created":"2023-03-21","cited_by_count":11,"area":null},{"id":"2312.10217","title":"T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learning","created":"2023-12-15","cited_by_count":11,"area":null},{"id":"2401.00912","title":"ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention","created":"2024-01-01","cited_by_count":11,"area":null},{"id":"2306.09304","title":"Radars for Autonomous Driving: A Review of Deep Learning Methods and Challenges","created":"2023-06-15","cited_by_count":10,"area":null},{"id":"2311.17770","title":"PillarNeSt: Embracing Backbone Scaling and Pretraining for Pillar-based 3D Object Detection","created":"2023-11-29","cited_by_count":10,"area":null},{"id":"2402.17562","title":"An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domains","created":"2024-02-27","cited_by_count":10,"area":null},{"id":"2503.12009","title":"UniMamba: Unified Spatial-Channel Representation Learning with Group-Efficient Mamba for LiDAR-based 3D Object Detection","created":"2025-03-15","cited_by_count":10,"area":"ssm"},{"id":"2308.03982","title":"PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection","created":"2023-08-08","cited_by_count":9,"area":null},{"id":"2401.16305","title":"MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection","created":"2024-01-29","cited_by_count":9,"area":null},{"id":"2408.06832","title":"FlatFusion: Delving into Details of Sparse Transformer-based Camera-LiDAR Fusion for Autonomous Driving","created":"2024-08-13","cited_by_count":9,"area":null},{"id":"2506.03714","title":"FSHNet: Fully Sparse Hybrid Network for 3D Object Detection","created":"2025-06-04","cited_by_count":9,"area":null},{"id":"2210.13488","title":"LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations","created":"2022-10-24","cited_by_count":8,"area":null},{"id":"2307.00347","title":"Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object Detection","created":"2023-07-01","cited_by_count":8,"area":null},{"id":"2312.08371","title":"PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection","created":"2023-12-13","cited_by_count":8,"area":null},{"id":"2403.10036","title":"SparseFusion: Efficient Sparse Multi-Modal Fusion Framework for Long-Range 3D Perception","created":"2024-03-15","cited_by_count":8,"area":null},{"id":"2502.19630","title":"Ev-3DOD: Pushing the Temporal Boundaries of 3D Object Detection with Event Cameras","created":"2025-02-26","cited_by_count":8,"area":null},{"id":"2503.08140","title":"HOTFormerLoc: Hierarchical Octree Transformer for Versatile Lidar Place Recognition Across Ground and Aerial Views","created":"2025-03-11","cited_by_count":8,"area":null},{"id":"2206.13082","title":"PST: Plant segmentation transformer for 3D point clouds of rapeseed plants at the podding stage","created":"2022-06-27","cited_by_count":7,"area":null},{"id":"2210.13428","title":"PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds","created":"2022-10-24","cited_by_count":7,"area":null},{"id":"2303.15416","title":"3D Video Object Detection with Learnable Object-Centric Global Optimization","created":"2023-03-27","cited_by_count":7,"area":null},{"id":"2311.04501","title":"PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds","created":"2023-11-08","cited_by_count":7,"area":null},{"id":"2401.12452","title":"Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration","created":"2024-01-23","cited_by_count":7,"area":null},{"id":"2407.04305","title":"Towards Stable 3D Object Detection","created":"2024-07-05","cited_by_count":7,"area":null},{"id":"2407.13748","title":"General Geometry-aware Weakly Supervised 3D Object Detection","created":"2024-07-18","cited_by_count":7,"area":null},{"id":"2209.00522","title":"Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking","created":"2022-09-01","cited_by_count":6,"area":null},{"id":"2406.19362","title":"STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning","created":"2024-06-27","cited_by_count":6,"area":null},{"id":"2303.04458","title":"Full Point Encoding for Local Feature Aggregation in 3D Point Clouds","created":"2023-03-08","cited_by_count":5,"area":null},{"id":"2311.03620","title":"FusionViT: Hierarchical 3D Object Detection via LiDAR-Camera Vision Transformer Fusion","created":"2023-11-07","cited_by_count":5,"area":null}],"next_cursor":"100"}