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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