Jinhao Chai — accepted AI-conference papers

2026

DiffSemanticFusion: Semantic Raster BEV Fusion for Autonomous Driving via Online Map Diffusion

Zhigang Sun, Yiru Wang, Anqing Jiang, Shuo Wang, Yu Gao, Yuwen Heng +10

RA-L 2026

Autonomous driving requires accurate scene understanding, including road geometry, traffic agents, and their semantic relationships. In online HD map generation scenarios, raster-based representations are well-suited to vision models but lack geometric precision, while graph-based representations re

Cited by 1 Source ↗code ↗Scholar ↗

2025

SparseMeXt: Unlocking the Potential of Sparse Representations for HD Map Construction

Anqing Jiang, Jinhao Chai, Yu Gao, Yiru Wang, Yuwen Heng, Zhigang Sun +7

IROS 2025

Recent advancements in high-definition (HD) map construction have demonstrated the effectiveness of dense representations, which heavily rely on computationally intensive bird’s-eye view (BEV) features. While sparse representations offer a more efficient alternative by avoiding dense BEV processing,

Cited by 4 Source ↗Scholar ↗