8 citations · 14 across the 15 of their papers we have counts for
17 papers
DriveZero: End-to-End Driving Beyond Human Demonstrations
Hao He, Chengcheng Hu, Zirun Su +17
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavioral coverage of the recorded…
RoGe: Novel View Synthesis via End-to-End Implicit Reconstruction and Generation
Xiaolei Lang, Ze Kang, Zehao Huang +1
Novel view synthesis from sparse inputs requires both geometric grounding from the observed views and generative priors of unobserved regions, motivating recent hybrid methods that…
Object Concepts Emerge from Motion
Boshi Li, Xiaohui Wang, Xiaoyang Wu +3
Object-centric visual representations are important for physical-world perception, but existing visual pretraining methods often capture semantic categories without preserving the…
Geometry-Grounded Unified 3D Perception for Autonomous Driving
Longfei Xu, Xiaohui Wang, Zehao Huang +4
Camera-based autonomous driving perception requires a shared representation that preserves metric 3D structure across synchronized multi-camera streams. However, existing image-bas…
ViSTR-Bench: Can MLLMs Reason from Continuous Visual Cues in Dynamic Scenes?
Han Li, Si Liu, Zehao Huang +6
Multimodal Large Language Models (MLLMs) have achieved remarkable success across diverse expert-level tasks, but they still struggle with fundamental abilities that humans naturall…
Generative Lane Topology Reasoning via Autoregressive Model with Geometry Prior
Jiahui Fu, Zehao Huang, Han Li +2
Lane topology reasoning aims to construct a lane graph from onboard sensor observations. Existing methods follow a detection and association paradigm that treats each lane instance…
Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation
Jinghui Lu, Jiayi Guan, Zhijian Huang +47
Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is…
Geometry-Guided 3D Visual Token Pruning for Video-Language Models
Han Li, Zehao Huang, Jiahui Fu +2
Multimodal large language models have demonstrated remarkable capabilities in 2D vision, motivating their extension to 3D scene understanding. Recent studies represent 3D scenes as…
Utonia: Toward One Encoder for All Point Clouds
Yujia Zhang, Xiaoyang Wu, Yunhan Yang +6
We dream of a future where point clouds from all domains can come together to shape a single model that benefits them all. Toward this goal, we present Utonia, a first step toward…
Concerto: Joint 2D-3D Self-Supervised Learning Emerges Spatial Representations
Yujia Zhang, Xiaoyang Wu, Yixing Lao +4
Humans learn abstract concepts through multisensory synergy, and once formed, such representations can often be recalled from a single modality. Inspired by this principle, we intr…
Object Concepts Emerge from Motion
Haoqian Liang, Xiaohui Wang, Zhichao Li +2
Object concepts play a foundational role in human visual cognition, enabling perception, memory, and interaction in the physical world. Inspired by findings in developmental neuros…
Anchor3DLane++: 3D Lane Detection via Sample-Adaptive Sparse 3D Anchor Regression
Shaofei Huang, Zhenwei Shen, Zehao Huang +4
In this paper, we focus on the challenging task of monocular 3D lane detection. Previous methods typically adopt inverse perspective mapping (IPM) to transform the Front-Viewed (FV…
MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection
Zitian Wang, Zehao Huang, Yulu Gao +2
The rise of autonomous vehicles has significantly increased the demand for robust 3D object detection systems. While cameras and LiDAR sensors each offer unique advantages--cameras…
Enhancing 3D Lane Detection and Topology Reasoning with 2D Lane Priors
Han Li, Zehao Huang, Zitian Wang +3
3D lane detection and topology reasoning are essential tasks in autonomous driving scenarios, requiring not only detecting the accurate 3D coordinates on lane lines, but also reaso…
SparseFusion: Efficient Sparse Multi-Modal Fusion Framework for Long-Range 3D Perception
Yiheng Li, Hongyang Li, Zehao Huang +2
Multi-modal 3D object detection has exhibited significant progress in recent years. However, most existing methods can hardly scale to long-range scenarios due to their reliance on…
Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving
Junyi Cao, Zhichao Li, Naiyan Wang +1
Recent studies have highlighted the promising application of NeRF in autonomous driving contexts. However, the complexity of outdoor environments, combined with the restricted view…
TSTTC: A Large-Scale Dataset for Time-to-Contact Estimation in Driving Scenarios
Yuheng Shi, Zehao Huang, Yan Yan +2
Time-to-Contact (TTC) estimation is a critical task for assessing collision risk and is widely used in various driver assistance and autonomous driving systems. The past few decade…