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20242026
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cs.CV2026

Towards Physically Consistent 4D Scene Reconstruction for Closed-loop Autonomous Driving Simulation

Bowyn Tan, Yutong Xie, Bai Huang +5

High-fidelity street scene reconstruction is pivotal for end-to-end autonomous driving simulation, where novel-view synthesis (NVS) and time-varying information modeling are two fu…

cs.CV2026

DriveCombo: Benchmarking Compositional Traffic Rule Reasoning in Autonomous Driving

Enhui Ma, Jiahuan Zhang, Guantian Zheng +10

Multimodal Large Language Models (MLLMs) are rapidly becoming the intelligence brain of end-to-end autonomous driving systems. A key challenge is to assess whether MLLMs can truly…

cs.CV2025

OmniScene: Attention-Augmented Multimodal 4D Scene Understanding for Autonomous Driving

Pei Liu, Hongliang Lu, Haichao Liu +5

Human vision is capable of transforming two-dimensional observations into an egocentric three-dimensional scene understanding, which underpins the ability to translate complex scen…

cs.CV2025

Beyond conventional vision: RGB-event fusion for robust object detection in dynamic traffic scenarios

Zhanwen Liu, Yujing Sun, Yang Wang +3

The dynamic range limitation of conventional RGB cameras reduces global contrast and causes loss of high-frequency details such as textures and edges in complex traffic environment…

cs.CV2025

Hierarchical Feature-level Reverse Propagation for Post-Training Neural Networks

Ni Ding, Lei He, Shengbo Eben Li +1

End-to-end autonomous driving has emerged as a dominant paradigm, yet its highly entangled black-box models pose significant challenges in terms of interpretability and safety assu…

cs.CV2024

Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception

Lei He, Qiaoyi Wang, Honglin Sun +5

Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…