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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

ARDepth: Auto-regressive Monocular Depth Estimation with Progressive Visual Conditioning

Zijie Wang, Wei Zhang, Weiming Zhang +4

ARDepth proposes an auto-regressive approach to monocular depth estimation that builds depth maps progressively across increasing spatial resolutions, using scale‑progressive condi…

cs.CV2026

OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives

Zedong Dan, Zijie Wang, Wei Zhang +6

Offline vectorized maps constitute critical infrastructure for high-precision autonomous driving and mapping services. Existing approaches rely predominantly on single ego-vehicle…

cs.CV2025

CoT4Det: A Chain-of-Thought Framework for Perception-Oriented Vision-Language Tasks

Yu Qi, Yumeng Zhang, Chenting Gong +4

Large Vision-Language Models (LVLMs) have demonstrated remarkable success in a broad range of vision-language tasks, such as general visual question answering and optical character…

cs.CV2025

LaneDiffusion: Improving Centerline Graph Learning via Prior Injected BEV Feature Generation

Zijie Wang, Weiming Zhang, Wei Zhang +4

Centerline graphs, crucial for path planning in autonomous driving, are traditionally learned using deterministic methods. However, these methods often lack spatial reasoning and s…

cs.CV2025

LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating

Deguo Xia, Weiming Zhang, Xiyan Liu +6

An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience of autonomous driving systems.…