activity
20242026
collaborators

7 papers

cs.CV2026

UniTeD: Unified Temporal Diffusion for Joint Perception and Planning in Autonomous Driving

Bo Zhao, Xinting Zhao, Naifan Li +2

Diffusion models have shown strong potential for multi-modal planning in end-to-end autonomous driving. However, most existing methods confine diffusion to the planning module, con…

cs.CV2026

TopoHR: Hierarchical Centerline Representation for Cyclic Topology Reasoning in Driving Scenes with Point-to-Instance Relations

Yifeng Bai, Zhirong Chen, Bo Song +2

Topology reasoning is crucial for autonomous driving. Current methods primarily focus on instance-level learning for centerline detection, followed by a sequential module for topol…

cs.CV2026

VICR: Visual In-Context Restoration for Real-World Image Super-Resolution

Qichang Zhang, Hailong Wang, Baiang Li +4

Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, existing generative Real-ISR…

cs.CV2026

SimPB++: Simultaneously Detecting 2D and 3D Objects from Multiple Cameras

Yingqi Tang, Zhaotie Meng, Erkang Cheng +1

Simultaneous perception of 2D objects in perspective view and 3D objects in Bird's Eye View (BEV) is challenging for multi-camera autonomous driving. Existing two-stage pipelines u…

cs.CV2025

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

Liuhan Yin, Runkun Ju, Guodong Guo +1

Unlike discriminative approaches in autonomous driving that predict a fixed set of candidate trajectories of the ego vehicle, generative methods, such as diffusion models, learn th…

cs.RO2025

HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder

Yingqi Tang, Zhuoran Xu, Zhaotie Meng +1

Although end-to-end autonomous driving (E2E-AD) technologies have made significant progress in recent years, there remains an unsatisfactory performance on closed-loop evaluation.…