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Shijian Lu

3 papers indexed

arxivcs.CVcs.AIcs.LG2026-07-23

3D-Aware VLMs with Implicit and Explicit Geometries

Wenhao Li, Xueying Jiang, Quanhao Qian, Deli Zhao, Ran Xu, Shijian Lu, et al.

Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial understanding and reasoning. To bridge this gap, we present VLM-IE3D, a unified framework that enhances…

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arxivcs.RO2026-07-20

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

Kehan Li, Bohan Hou, Minghao Zhu, Tianyi Zhang, Zesen Cheng, Zhikai Wang, et al.

We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and physically grounded framework, RynnBrain 1.1 supports embodied perception, spatial reasoning, localization, and planning. Compared wi…

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arxivcs.CVcs.AIcs.LGcs.RO2026-07-06

From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model

Wenhao Li, Xueying Jiang, Quanhao Qian, Deli Zhao, Shijian Lu, Gongjie Zhang, et al.

Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing view-robust Vision-Language-Action (VLA) policies tolerate such camera variations only when the camera…

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