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20232025
most citedForging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities

3 citations · 11 across the 11 of their papers we have counts for

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cs.CV2025

Pose Optimization for Autonomous Driving Datasets using Neural Rendering Models

Quentin Herau, Nathan Piasco, Moussab Bennehar +6

Autonomous driving systems rely on accurate perception and localization of the ego car to ensure safety and reliability in challenging real-world driving scenarios. Public datasets…

cs.CV20242 cited

An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training

Haiming Zhang, Ying Xue, Xu Yan +6

The field of autonomous driving is experiencing a surge of interest in world models, which aim to predict potential future scenarios based on historical observations. In this paper…

cs.CV2024

Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusion

Shiqi Tan, Hamidreza Fazlali, Yixuan Xu +2

Range-View(RV)-based 3D point cloud segmentation is widely adopted due to its compact data form. However, RV-based methods fall short in providing robust segmentation for the occlu…

cs.CV20241 cited

VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving

Yibo Liu, Zheyuan Yang, Guile Wu +5

Generating 3D vehicle assets from in-the-wild observations is crucial to autonomous driving. Existing image-to-3D methods cannot well address this problem because they learn genera…

cs.CV20241 cited

AutoSplat: Constrained Gaussian Splatting for Autonomous Driving Scene Reconstruction

Mustafa Khan, Hamidreza Fazlali, Dhruv Sharma +4

Realistic scene reconstruction and view synthesis are essential for advancing autonomous driving systems by simulating safety-critical scenarios. 3D Gaussian Splatting excels in re…

cs.CV2024

Neural Radiance Fields with Torch Units

Bingnan Ni, Huanyu Wang, Dongfeng Bai +4

Neural Radiance Fields (NeRF) give rise to learning-based 3D reconstruction methods widely used in industrial applications. Although prevalent methods achieve considerable improvem…