collaborators

6 papers

cs.RO2026

MonoEgo: Monocular Metric Egocentric Demonstration Capture with Passive Wrist Constellations and Sparse Workstation Anchors

Jie Xu, Kangjin Yu, Ziyi Jin +2

Image-aligned metric demonstrations often require dedicated tracking hardware and synchronization across devices. We present MonoEgo, a capture system that replaces active wrist in…

cs.RO2026

Does Online Gravity Estimation Matter? Revisiting a Silent Design Split in LiDAR-Inertial Odometry

Jie Xu, Ziyi Jin, Kangjin Yu +5

LiDAR-inertial odometry (LIO) systems differ in whether they continue estimating gravity after initialization. We compare four gravity-bias state configurations in each of FAST-LIO…

cs.CV2026

MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving

Junli Wang, Yinan Zheng, Xueyi Liu +9

Generative models have shown great potential in trajectory planning. Recent studies demonstrate that anchor-guided generative models are effective in modeling the uncertainty of dr…

cs.RO2025

WorldRFT: Latent World Model Planning with Reinforcement Fine-Tuning for Autonomous Driving

Pengxuan Yang, Ben Lu, Zhongpu Xia +7

Latent World Models enhance scene representation through temporal self-supervised learning, presenting a perception annotation-free paradigm for end-to-end autonomous driving. Howe…

cs.RO2025

TransDiffuser: Diverse Trajectory Generation with Decorrelated Multi-modal Representation for End-to-end Autonomous Driving

Xuefeng Jiang, Yuan Ma, Pengxiang Li +7

In recent years, diffusion models have demonstrated remarkable potential across diverse domains, from vision generation to language modeling. Transferring its generative capabiliti…

cs.CV2025

TokenFLEX: Unified VLM Training for Flexible Visual Tokens Inference

Junshan Hu, Jialiang Mao, Zhikang Liu +3

Conventional Vision-Language Models(VLMs) typically utilize a fixed number of vision tokens, regardless of task complexity. This one-size-fits-all strategy introduces notable ineff…