5 citations · 5 across the 8 of their papers we have counts for
8 papers · 1 filter
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…
OmniGen: Unified Multimodal Sensor Generation for Autonomous Driving
Tao Tang, Enhui Ma, xia zhou +9
Autonomous driving has seen remarkable advancements, largely driven by extensive real-world data collection. However, acquiring diverse and corner-case data remains costly and inef…
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…
AD-R1: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving with Impartial World Models
Tianyi Yan, Tao Tang, Xingtai Gui +11
End-to-end models for autonomous driving hold the promise of learning complex behaviors directly from sensor data, but face critical challenges in safety and handling long-tail eve…
RoboPearls: Editable Video Simulation for Robot Manipulation
Tao Tang, Likui Zhang, Youpeng Wen +9
The development of generalist robot manipulation policies has seen significant progress, driven by large-scale demonstration data across diverse environments. However, the high cos…
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…
S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking
Tao Tang, Lijun Zhou, Pengkun Hao +9
3D multiple object tracking (MOT) plays a crucial role in autonomous driving perception. Recent end-to-end query-based trackers simultaneously detect and track objects, which have…
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving
Tao Tang, Dafeng Wei, Zhengyu Jia +12
The rapid development of the autonomous driving industry has led to a significant accumulation of autonomous driving data. Consequently, there comes a growing demand for retrieving…