CVPR2025轨迹预测相关论文以及自动驾驶端到端相关论文

CVPR2025

1、基于自动驾驶的轨迹预测相关论文：

1. Leveraging SD Map to Augment HD Map-based Trajectory Prediction
2. ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling
3. Adapting to Observation Length of Trajectory Prediction via Contrastive Learning
4. From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models
5. Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment
6. Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting
7. Multiple Object Tracking as ID Prediction
8. Enduring, Efficient and Robust Trajectory Prediction Attack in Autonomous Driving via Optimization-Driven Multi-Frame Perturbation Framework
9. Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning
10. Poly-Autoregressive Prediction for Modeling Interactions

2、基于端到端自动驾驶相关论文

1. Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
2. DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving
3. Distilling Multi-modal Large Language Models for Autonomous Driving
4. MPDrive: Improving Spatial Understanding with Marker-Based Prompt Learning for Autonomous Driving
5. DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
6. CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-Scale Reinforcement Learning in Autonomous Driving
7. Don’t Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
8. GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving
9. SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving