1 citations · 2 across the 7 of their papers we have counts for
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DrivingRecon: Large 4D Gaussian Reconstruction Model For Autonomous Driving
Hao Lu, Tianshuo Xu, Wenzhao Zheng +6
Photorealistic 4D reconstruction of street scenes is essential for developing real-world simulators in autonomous driving. However, most existing methods perform this task offline…
GPD-1: Generative Pre-training for Driving
Zixun Xie, Sicheng Zuo, Wenzhao Zheng +5
Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems. Most existing methods focus on one aspect of scene e…
Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model
Lening Wang, Wenzhao Zheng, Dalong Du +8
4D driving simulation is essential for developing realistic autonomous driving simulators. Despite advancements in existing methods for generating driving scenes, significant chall…
FactorLLM: Factorizing Knowledge via Mixture of Experts for Large Language Models
Zhongyu Zhao, Menghang Dong, Rongyu Zhang +6
Recent research has demonstrated that Feed-Forward Networks (FFNs) in Large Language Models (LLMs) play a pivotal role in storing diverse linguistic and factual knowledge. Conventi…
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
Hao Lu, Jiaqi Tang, Xinli Xu +6
The emergence of Multi-Camera 3D Object Detection (MC3D-Det), facilitated by bird's-eye view (BEV) representation, signifies a notable progression in 3D object detection. Scaling M…
GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving
Yunpeng Zhang, Deheng Qian, Ding Li +11
Modeling complicated interactions among the ego-vehicle, road agents, and map elements has been a crucial part for safety-critical autonomous driving. Previous works on end-to-end…