Andreas Geiger
収録論文 32本 ・ フィジカルAI/ロボット学習
※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。
論文
- PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning2026/8/1
- World Engine: Towards the Era of Post-Training for Autonomous Driving2026/6/1
- 123D: Unifying Multi-Modal Autonomous Driving Data at Scale2026/5/1
- Fail2Drive: Benchmarking Closed-Loop Driving Generalization2026/4/1
- LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving2025/12/1
- PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving2025/11/1
- Pseudo-Simulation for Autonomous Driving2025/6/1
- ReSim: Reliable World Simulation for Autonomous Driving2025/6/1
- Is Single-View Mesh Reconstruction Ready for Robotics?2025/5/1
- CaRL: Learning Scalable Planning Policies with Simple Rewards2025/4/1
- Centaur: Robust End-to-End Autonomous Driving with Test-Time Training2025/3/1
- HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving2024/12/1
- Hidden Biases of End-to-End Driving Datasets2024/12/1
- EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners2024/11/1
- NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking2024/6/1
- Efficient End-to-End Detection of 6-DoF Grasps for Robotic Bin Picking2024/5/1
- SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic2024/3/1
- On Offline Evaluation of 3D Object Detection for Autonomous Driving2023/8/1
- End-to-end Autonomous Driving: Challenges and Frontiers2023/6/1
- Parting with Misconceptions about Learning-based Vehicle Motion Planning2023/6/1
- Hidden Biases of End-to-End Driving Models2023/6/1
- PlanT: Explainable Planning Transformers via Object-Level Representations2022/10/1
- TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving2022/5/1
- KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients2022/4/1
- NEAT: Neural Attention Fields for End-to-End Autonomous Driving2021/9/1
- Multi-Modal Fusion Transformer for End-to-End Autonomous Driving2021/4/1
- Label Efficient Visual Abstractions for Autonomous Driving2020/5/1
- Robust Dense Mapping for Large-Scale Dynamic Environments2019/5/1
- Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System2018/9/1
- Real-Time Dense Mapping for Self-driving Vehicles using Fisheye Cameras2018/9/1
- Conditional Affordance Learning for Driving in Urban Environments2018/6/1
- Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art2017/4/1