8 citations · 9 across the 10 of their papers we have counts for
10 papers
InfraOcc: An Infrastructure Occupancy Benchmark with Static-to-Dynamic Reasoning
Lei Yang, Xiaokai Bai, Boqi Li +8
Fixed-viewpoint infrastructure sensors repeatedly observe the same traffic space, making roadside 3D occupancy structurally different from ego-vehicle perception: a near-persistent…
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…
CorrectAD: A Self-Correcting Agentic System to Improve End-to-end Planning in Autonomous Driving
Enhui Ma, Lijun Zhou, Tao Tang +11
End-to-end planning methods are the de facto standard of the current autonomous driving system, while the robustness of the data-driven approaches suffers due to the notorious long…
DriveMRP: Enhancing Vision-Language Models with Synthetic Motion Data for Motion Risk Prediction
Zhiyi Hou, Enhui Ma, Fang Li +11
Autonomous driving has seen significant progress, driven by extensive real-world data. However, in long-tail scenarios, accurately predicting the safety of the ego vehicle's future…
MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous Driving
Haiguang Wang, Daqi Liu, Hongwei Xie +5
In recent years, data-driven techniques have greatly advanced autonomous driving systems, but the need for rare and diverse training data remains a challenge, requiring significant…
DiVE: DiT-based Video Generation with Enhanced Control
Junpeng Jiang, Gangyi Hong, Lijun Zhou +10
Generating high-fidelity, temporally consistent videos in autonomous driving scenarios faces a significant challenge, e.g. problematic maneuvers in corner cases. Despite recent vid…
Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation
Enhui Ma, Lijun Zhou, Tao Tang +9
Using generative models to synthesize new data has become a de-facto standard in autonomous driving to address the data scarcity issue. Though existing approaches are able to boost…
AlignMiF: Geometry-Aligned Multimodal Implicit Field for LiDAR-Camera Joint Synthesis
Tao Tang, Guangrun Wang, Yixing Lao +5
Neural implicit fields have been a de facto standard in novel view synthesis. Recently, there exist some methods exploring fusing multiple modalities within a single field, aiming…
OpenSight: A Simple Open-Vocabulary Framework for LiDAR-Based Object Detection
Hu Zhang, Jianhua Xu, Tao Tang +4
Traditional LiDAR-based object detection research primarily focuses on closed-set scenarios, which falls short in complex real-world applications. Directly transferring existing 2D…
BEVHeight++: Toward Robust Visual Centric 3D Object Detection
Lei Yang, Tao Tang, Jun Li +6
While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent…