{"total":102,"rows":[{"id":"2312.10035","title":"Point Transformer V3: Simpler, Faster, Stronger","created":"2023-12-15","cited_by_count":589,"area":null},{"id":"2209.05451","title":"Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation","created":"2022-09-12","cited_by_count":551,"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":"2301.06051","title":"DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets","created":"2023-01-15","cited_by_count":122,"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":"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":"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":"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":"2403.15241","title":"IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection","created":"2024-03-22","cited_by_count":57,"area":null},{"id":"2403.10094","title":"RangeLDM: Fast Realistic LiDAR Point Cloud Generation","created":"2024-03-15","cited_by_count":47,"area":"wm"},{"id":"2308.16632","title":"3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation","created":"2023-08-31","cited_by_count":36,"area":null},{"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":"2310.08261","title":"GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection","created":"2023-10-12","cited_by_count":34,"area":null},{"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":"2303.12621","title":"OcTr: Octree-based Transformer for 3D Object Detection","created":"2023-03-22","cited_by_count":32,"area":null},{"id":"2205.07417","title":"Transformers in 3D Point Clouds: A Survey","created":"2022-05-16","cited_by_count":31,"area":null},{"id":"2211.08542","title":"CXTrack: Improving 3D Point Cloud Tracking with Contextual Information","created":"2022-11-12","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":"2310.05699","title":"Uni3DETR: Unified 3D Detection Transformer","created":"2023-10-09","cited_by_count":27,"area":null},{"id":"2304.01464","title":"Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection","created":"2023-04-04","cited_by_count":24,"area":"distill"},{"id":"2311.02608","title":"Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook","created":"2023-11-05","cited_by_count":24,"area":null},{"id":"2211.06108","title":"RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems","created":"2022-11-11","cited_by_count":23,"area":null},{"id":"2208.04309","title":"3D Vision with Transformers: A Survey","created":"2022-08-08","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":"2404.01300","title":"NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields","created":"2024-04-01","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":"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":"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":"2407.10159","title":"RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation","created":"2024-07-14","cited_by_count":15,"area":null},{"id":"2205.14657","title":"COFS: Controllable Furniture layout Synthesis","created":"2022-05-29","cited_by_count":14,"area":null},{"id":"2401.02702","title":"VoxelNextFusion: A Simple, Unified and Effective Voxel Fusion Framework for Multi-Modal 3D Object Detection","created":"2024-01-05","cited_by_count":14,"area":null},{"id":"2411.01542","title":"FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing","created":"2024-11-03","cited_by_count":14,"area":null},{"id":"2307.07942","title":"KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection","created":"2023-07-16","cited_by_count":13,"area":null},{"id":"2303.08578","title":"SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation","created":"2023-03-14","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":"2402.17986","title":"PolyOculus: Simultaneous Multi-view Image-based Novel View Synthesis","created":"2024-02-28","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":"2404.12798","title":"A Point-Based Approach to Efficient LiDAR Multi-Task Perception","created":"2024-04-19","cited_by_count":9,"area":null},{"id":"2410.19872","title":"Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey","created":"2024-10-24","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":"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":"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":"2207.05497","title":"Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network","created":"2022-07-12","cited_by_count":7,"area":null},{"id":"2406.08152","title":"CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise Transformer","created":"2024-06-12","cited_by_count":7,"area":null},{"id":"2406.10907","title":"SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection","created":"2024-06-16","cited_by_count":7,"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":"2211.01664","title":"PointSee: Image Enhances Point Cloud","created":"2022-11-03","cited_by_count":5,"area":null},{"id":"2406.17530","title":"Point Tree Transformer for Point Cloud Registration","created":"2024-06-25","cited_by_count":5,"area":null},{"id":"2409.11018","title":"Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation","created":"2024-09-17","cited_by_count":4,"area":"ssm"},{"id":"2410.06731","title":"Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data","created":"2024-10-09","cited_by_count":4,"area":null},{"id":"2508.02288","title":"Unleashing the Temporal Potential of Stereo Event Cameras for Continuous-Time 3D Object Detection","created":"2025-08-04","cited_by_count":4,"area":null},{"id":"2511.05449","title":"How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?","created":"2025-11-07","cited_by_count":4,"area":null},{"id":"2603.25165","title":"Towards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds","created":"2026-03-26","cited_by_count":4,"area":null},{"id":"2301.06869","title":"SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation","created":"2023-01-17","cited_by_count":3,"area":null},{"id":"2303.05078","title":"Efficient Transformer-based 3D Object Detection with Dynamic Token Halting","created":"2023-03-09","cited_by_count":3,"area":null},{"id":"2304.02867","title":"Voxel or Pillar: Exploring Efficient Point Cloud Representation for 3D Object Detection","created":"2023-04-06","cited_by_count":3,"area":null},{"id":"2305.15213","title":"GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentation","created":"2023-05-24","cited_by_count":3,"area":null},{"id":"2310.17418","title":"Circuit as Set of Points","created":"2023-10-26","cited_by_count":3,"area":null},{"id":"2401.11718","title":"MsSVT++: Mixed-scale Sparse Voxel Transformer with Center Voting for 3D Object Detection","created":"2024-01-22","cited_by_count":3,"area":null},{"id":"2406.19048","title":"BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection","created":"2024-06-27","cited_by_count":3,"area":null},{"id":"2603.25494","title":"AdaSFormer: Adaptive Serialized Transformers for Monocular Semantic Scene Completion from Indoor Environments","created":"2026-03-26","cited_by_count":3,"area":null},{"id":"2211.03407","title":"3D Harmonic Loss: Towards Task-consistent and Time-friendly 3D Object Detection on Edge for V2X Orchestration","created":"2022-11-07","cited_by_count":2,"area":null},{"id":"2302.09907","title":"General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment","created":"2023-02-20","cited_by_count":2,"area":null},{"id":"2304.01519","title":"LiDAR-Based 3D Object Detection via Hybrid 2D Semantic Scene Generation","created":"2023-04-04","cited_by_count":2,"area":null},{"id":"2309.02583","title":"Representation Learning for Sequential Volumetric Design Tasks","created":"2023-09-05","cited_by_count":2,"area":null},{"id":"2401.07240","title":"DCDet: Dynamic Cross-based 3D Object Detector","created":"2024-01-14","cited_by_count":2,"area":null},{"id":"2410.01816","title":"Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects","created":"2024-09-14","cited_by_count":2,"area":null},{"id":"2209.01745","title":"SEFormer: Structure Embedding Transformer for 3D Object Detection","created":"2022-09-05","cited_by_count":1,"area":null},{"id":"2211.05580","title":"Hyperbolic Cosine Transformer for LiDAR 3D Object Detection","created":"2022-11-10","cited_by_count":1,"area":null},{"id":"2211.11066","title":"Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation","created":"2022-11-20","cited_by_count":1,"area":null},{"id":"2212.05262","title":"Position Embedding Needs an Independent Layer Normalization","created":"2022-12-10","cited_by_count":1,"area":null},{"id":"2311.06054","title":"Refining the ONCE Benchmark with Hyperparameter Tuning","created":"2023-11-10","cited_by_count":1,"area":null},{"id":"2402.17521","title":"AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding","created":"2024-02-27","cited_by_count":1,"area":null},{"id":"2403.01978","title":"Leveraging Anchor-based LiDAR 3D Object Detection via Point Assisted Sample Selection","created":"2024-03-04","cited_by_count":1,"area":null},{"id":"2403.06166","title":"Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving","created":"2024-03-10","cited_by_count":1,"area":null},{"id":"2408.01688","title":"SiamMo: Siamese Motion-Centric 3D Object Tracking","created":"2024-08-03","cited_by_count":1,"area":null},{"id":"2606.31895","title":"RESOLVE: A Multi-Resolution and Multi-Modal Dataset for Roadside Cooperative Perception","created":"2026-06-30","cited_by_count":1,"area":null},{"id":"2608.14428","title":"GhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure","created":"2026-08-14","cited_by_count":1,"area":null},{"id":"2208.14796","title":"3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning","created":"2022-08-31","cited_by_count":0,"area":null},{"id":"2211.07108","title":"Recursive Cross-View: Use Only 2D Detectors to Achieve 3D Object Detection without 3D Annotations","created":"2022-11-14","cited_by_count":0,"area":null},{"id":"2301.02650","title":"Hierarchical Point Attention for Indoor 3D Object Detection","created":"2023-01-06","cited_by_count":0,"area":null},{"id":"2305.06115","title":"VTPNet for 3D deep learning on point cloud","created":"2023-05-10","cited_by_count":0,"area":null},{"id":"2307.11482","title":"R2Det: Redemption from Range-view for Accurate 3D Object Detection","created":"2023-07-21","cited_by_count":0,"area":null},{"id":"2408.10007","title":"P3P: Pseudo-3D Pre-training for Scaling 3D Voxel-based Masked Autoencoders","created":"2024-08-19","cited_by_count":0,"area":null},{"id":"2409.00690","title":"Decoupled and Interactive Regression Modeling for High-performance One-stage 3D Object Detection","created":"2024-09-01","cited_by_count":0,"area":null},{"id":"2409.04601","title":"Multi-scale Feature Fusion with Point Pyramid for 3D Object Detection","created":"2024-09-06","cited_by_count":0,"area":null},{"id":"2503.01899","title":"FASTer: Focal Token Acquiring-and-Scaling Transformer for Long-term 3D Object Detection","created":"2025-02-28","cited_by_count":0,"area":null},{"id":"2503.17168","title":"Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Driving","created":"2025-03-21","cited_by_count":0,"area":null},{"id":"2508.11951","title":"Transferable Class Statistics and Multi-scale Feature Approximation for 3D Object Detection","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2509.01080","title":"SpectMamba: Integrating Frequency and State Space Models for Enhanced Medical Image Detection","created":"2025-09-01","cited_by_count":0,"area":"ssm"},{"id":"2509.05780","title":"3DPillars: Pillar-based two-stage 3D object detection","created":"2025-09-06","cited_by_count":0,"area":null},{"id":"2604.16696","title":"LOD-Net: Locality-Aware 3D Object Detection Using Multi-Scale Transformer Network","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2606.00688","title":"Shape-Prior-Based Point Cloud Completion for Single-Stage Fully Sparse 3D Object Detection","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2606.01172","title":"Revisiting Neural Processes via Fourier Transform and Volterra Series","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2606.16354","title":"GraphBEV++: Multi-Modal Feature Alignment for Autonomous Driving","created":"2026-06-15","cited_by_count":0,"area":"driving"}],"next_cursor":"100"}