Cover Image

DiffRefiner: Coarse to Fine Trajectory Planning via Diffusion Refinement with Semantic Interaction for End to End Autonomous Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yin, Liuhan, Ju, Runkun, Guo, Guodong, Cheng, Erkang
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
by: Liao, Bencheng, et al.
Published: (2024)

SynDiff-AD: Improving Semantic Segmentation and End-to-End Autonomous Driving with Synthetic Data from Latent Diffusion Models
by: Goel, Harsh, et al.
Published: (2024)

ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Driving
by: Zheng, Zhiyu, et al.
Published: (2025)

Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving
by: Zhang, Bozhou, et al.
Published: (2025)

SUPER-AD: Semantic Uncertainty-aware Planning for End-to-End Robust Autonomous Driving
by: Ryu, Wonjeong, et al.
Published: (2025)

Fully Unified Motion Planning for End-to-End Autonomous Driving
by: Liu, Lin, et al.
Published: (2025)

ComDrive: Comfort-Oriented End-to-End Autonomous Driving
by: Wang, Junming, et al.
Published: (2024)

CoReVLA: A Dual-Stage End-to-End Autonomous Driving Framework for Long-Tail Scenarios via Collect-and-Refine
by: Fang, Shiyu, et al.
Published: (2025)

TrajDiff: End-to-end Autonomous Driving without Perception Annotation
by: Gui, Xingtai, et al.
Published: (2025)

HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models
by: Cho, Hoonhee, et al.
Published: (2026)

Multimodal Action Diffusion for Robust End-to-End Autonomous Driving
by: Rodríguez-Vidal, Jorge Daniel, et al.
Published: (2026)

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning
by: Jiang, Bo, et al.
Published: (2024)

Enhancing End-to-End Autonomous Driving with Risk Semantic Distillaion from VLM
by: Qin, Jack, et al.
Published: (2025)

Divide and Merge: Motion and Semantic Learning in End-to-End Autonomous Driving
by: Shen, Yinzhe, et al.
Published: (2025)

Cognitive-Hierarchy Guided End-to-End Planning for Autonomous Driving
by: Wang, Zhennan, et al.
Published: (2025)

GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving
by: Xing, Zebin, et al.
Published: (2025)

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
by: Wu, Yanhao, et al.
Published: (2026)

GenAD: Generative End-to-End Autonomous Driving
by: Zheng, Wenzhao, et al.
Published: (2024)

InsightDrive: Insight Scene Representation for End-to-End Autonomous Driving
by: Song, Ruiqi, et al.
Published: (2025)

End-to-End Shared Attention Estimation via Group Detection with Feedback Refinement
by: Nakatani, Chihiro, et al.
Published: (2026)

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
by: Song, Ziying, et al.
Published: (2025)

PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
by: Chen, Zhili, et al.
Published: (2023)

SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
by: Sun, Wenchao, et al.
Published: (2024)

Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion
by: Zhang, Jiaru, et al.
Published: (2026)

Future-Aware End-to-End Driving: Bidirectional Modeling of Trajectory Planning and Scene Evolution
by: Zhang, Bozhou, et al.
Published: (2025)

Generative Scenario Rollouts for End-to-End Autonomous Driving
by: Yasarla, Rajeev, et al.
Published: (2026)

Boundary-Refined Prototype Generation: A General End-to-End Paradigm for Semi-Supervised Semantic Segmentation
by: Dong, Junhao, et al.
Published: (2023)

Beyond Imitation: Constraint-Aware Trajectory Generation with Flow Matching For End-to-End Autonomous Driving
by: Liu, Lin, et al.
Published: (2025)

Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
by: Wintel, Florian, et al.
Published: (2025)

DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
by: Zou, Jialv, et al.
Published: (2025)

Autoregressive End-to-End Planning with Time-Invariant Spatial Alignment and Multi-Objective Policy Refinement
by: Zhao, Jianbo, et al.
Published: (2025)

GuideFlow: Constraint-Guided Flow Matching for Planning in End-to-End Autonomous Driving
by: Liu, Lin, et al.
Published: (2025)

Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
by: Zhang, Bozhou, et al.
Published: (2025)

Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving
by: Wang, Linhan, et al.
Published: (2026)

MAP: End-to-End Autonomous Driving with Map-Assisted Planning
by: Yin, Huilin, et al.
Published: (2025)

DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning
by: Yao, Wenhao, et al.
Published: (2025)

End-to-End Driving with Online Trajectory Evaluation via BEV World Model
by: Li, Yingyan, et al.
Published: (2025)

HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder
by: Tang, Yingqi, et al.
Published: (2025)

Exploring the Causality of End-to-End Autonomous Driving
by: Li, Jiankun, et al.
Published: (2024)

Generative Planning with 3D-vision Language Pre-training for End-to-End Autonomous Driving
by: Li, Tengpeng, et al.
Published: (2025)