{"total":24,"rows":[{"id":"2203.17270","title":"BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers","created":"2022-03-31","cited_by_count":1218,"area":"wm"},{"id":"2309.17080","title":"GAIA-1: A Generative World Model for Autonomous Driving","created":"2023-09-29","cited_by_count":637,"area":"wm"},{"id":"2405.17398","title":"Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability","created":"2024-05-27","cited_by_count":347,"area":"wm"},{"id":"2304.14365","title":"Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving","created":"2023-04-27","cited_by_count":332,"area":"wm"},{"id":"2311.16038","title":"OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving","created":"2023-11-27","cited_by_count":233,"area":"wm"},{"id":"2402.11502","title":"GenAD: Generative End-to-End Autonomous Driving","created":"2024-02-18","cited_by_count":225,"area":"wm"},{"id":"2311.01017","title":"Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion","created":"2023-11-02","cited_by_count":106,"area":"wm"},{"id":"2405.20323","title":"$\\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving","created":"2024-05-30","cited_by_count":105,"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":"2311.17663","title":"Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications","created":"2023-11-29","cited_by_count":52,"area":"wm"},{"id":"2409.11356","title":"RenderWorld: World Model with Self-Supervised 3D Label","created":"2024-09-17","cited_by_count":46,"area":"wm"},{"id":"2406.08691","title":"UnO: Unsupervised Occupancy Fields for Perception and Forecasting","created":"2024-06-12","cited_by_count":41,"area":"wm"},{"id":"2310.12970","title":"Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding","created":"2023-10-19","cited_by_count":33,"area":"wm"},{"id":"2211.10593","title":"MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception","created":"2022-11-19","cited_by_count":29,"area":"wm"},{"id":"2502.15180","title":"OccProphet: Pushing Efficiency Frontier of Camera-Only 4D Occupancy Forecasting with Observer-Forecaster-Refiner Framework","created":"2025-02-21","cited_by_count":12,"area":"wm"},{"id":"2503.18108","title":"Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving","created":"2025-03-23","cited_by_count":12,"area":"wm"},{"id":"2405.13193","title":"Efficient Imitation Learning with Conservative World Models","created":"2024-05-21","cited_by_count":11,"area":"wm"},{"id":"2602.08006","title":"ForecastOcc: Vision-based Semantic Occupancy Forecasting","created":"2026-02-08","cited_by_count":7,"area":"wm"},{"id":"2411.14169","title":"Spatiotemporal Decoupling for Efficient Vision-Based Occupancy Forecasting","created":"2024-11-21","cited_by_count":6,"area":"wm"},{"id":"2503.09215","title":"Other Vehicle Trajectories Are Also Needed: A Driving World Model Unifies Ego-Other Vehicle Trajectories in Video Latent Space","created":"2025-03-12","cited_by_count":5,"area":"wm"},{"id":"2301.04783","title":"Predictive World Models from Real-World Partial Observations","created":"2023-01-12","cited_by_count":4,"area":"wm"},{"id":"2504.18448","title":"NoiseController: Towards Consistent Multi-view Video Generation via Noise Decomposition and Collaboration","created":"2025-04-25","cited_by_count":3,"area":"wm"},{"id":"2606.18250","title":"Future Dynamic 3D Reconstruction: Toward 3D World Modeling with Disentangled Ego-Motion","created":"2026-06-16","cited_by_count":1,"area":"wm"},{"id":"2609.32013","title":"TriO: Tri-Modal Unsupervised Occupancy World Model for Anything Perception","created":"2026-09-25","cited_by_count":0,"area":"wm"}],"next_cursor":null}