{"total":16,"rows":[{"id":"2109.07644","title":"OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication","created":"2021-09-16","cited_by_count":304,"area":"wm"},{"id":"2401.01339","title":"Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting","created":"2024-01-02","cited_by_count":221,"area":"wm"},{"id":"2209.03954","title":"Learning to Generate Realistic LiDAR Point Clouds","created":"2022-09-08","cited_by_count":93,"area":"wm"},{"id":"2404.00815","title":"Towards Realistic Scene Generation with LiDAR Diffusion Models","created":"2024-03-31","cited_by_count":69,"area":"wm"},{"id":"2501.11260","title":"A Survey of World Models for Autonomous Driving","created":"2025-01-20","cited_by_count":60,"area":"wm"},{"id":"2403.10094","title":"RangeLDM: Fast Realistic LiDAR Point Cloud Generation","created":"2024-03-15","cited_by_count":47,"area":"wm"},{"id":"2402.02112","title":"S-NeRF++: Autonomous Driving Simulation via Neural Reconstruction and Generation","created":"2024-02-03","cited_by_count":28,"area":"wm"},{"id":"2102.11952","title":"Learning to Drop Points for LiDAR Scan Synthesis","created":"2021-02-23","cited_by_count":27,"area":"wm"},{"id":"2407.19628","title":"Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer","created":"2024-07-29","cited_by_count":27,"area":"wm"},{"id":"2210.11750","title":"Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data","created":"2022-10-21","cited_by_count":18,"area":"wm"},{"id":"2505.16902","title":"RealEngine: Simulating Autonomous Driving in Realistic Context","created":"2025-05-22","cited_by_count":10,"area":"wm"},{"id":"2412.07385","title":"LOGen: Toward Lidar Object Generation by Point Diffusion","created":"2024-12-10","cited_by_count":9,"area":"wm"},{"id":"2412.00592","title":"LiDAR-EDIT: LiDAR Data Generation by Editing the Object Layouts in Real-World Scenes","created":"2024-11-30","cited_by_count":4,"area":"wm"},{"id":"2512.20105","title":"LiDARDraft: Generating LiDAR Point Cloud from Versatile Inputs","created":"2025-12-23","cited_by_count":1,"area":"wm"},{"id":"2511.16049","title":"LiSTAR: Ray-Centric World Models for 4D LiDAR Sequences in Autonomous Driving","created":"2025-11-20","cited_by_count":0,"area":"wm"},{"id":"2606.30147","title":"T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation","created":"2026-06-29","cited_by_count":0,"area":"wm"}],"next_cursor":null}