CVPR2025自动驾驶端到端前沿论文汇总
自动驾驶
文章目录
- 自动驾驶
- 前言
- 自动驾驶的轨迹预测论文
- 端到端自动驾驶论文
前言
汇总CVPR2025自动驾驶前沿论文
自动驾驶的轨迹预测论文
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| Leveraging SD Map to Augment HD Map-based Trajectory Prediction | |
| ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling | |
| Adapting to Observation Length of Trajectory Prediction via Contrastive Learning | |
| From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models | |
| Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment | |
| Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting | |
| Multiple Object Tracking as ID Prediction | |
| Enduring, Efficient and Robust Trajectory Prediction Attack in Autonomous Driving via Optimization-Driven Multi-Frame Perturbation Framework | |
| Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning | |
| Poly-Autoregressive Prediction for Modeling Interactions | |
端到端自动驾驶论文
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| Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning | |
| DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving | |
| Distilling Multi-modal Large Language Models for Autonomous Driving | |
| MPDrive: Improving Spatial Understanding with Marker-Based Prompt Learning for Autonomous Driving | |
| DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving | |
| CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-Scale Reinforcement Learning in Autonomous Driving | |
| Don’t Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving | |
| GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving | |
| SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving | |
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