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From the 1 of 6 linked papers with an AI index.

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6 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

TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation

Alexander Matyasko, Xin Lou, Indriyati Atmosukarto +1

Attacking semantic segmentation models is significantly harder than image classification models because an attacker must flip thousands of pixel predictions simultaneously. Standar…

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

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

VLDrive: Vision-Augmented Lightweight MLLMs for Efficient Language-grounded Autonomous Driving

Ruifei Zhang, Wei Zhang, Xiao Tan +4

Recent advancements in language-grounded autonomous driving have been significantly promoted by the sophisticated cognition and reasoning capabilities of large language models (LLM…

cs.CV2025

AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving

Ruifei Zhang, Junlin Xie, Wei Zhang +4

Effectively integrating Large Language Models (LLMs) into autonomous driving requires a balance between leveraging high-level reasoning and maintaining real-time efficiency. Existi…