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20242026
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cs.CV2026

3D-Aware VLMs with Implicit and Explicit Geometries

Wenhao Li, Xueying Jiang, Quanhao Qian +4

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 unde…

cs.CV2026

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

Wenhao Li, Xueying Jiang, Quanhao Qian +4

Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing vie…

cs.CV2026

Towards Camera-Robust 3D Localization: Equation-Anchored Tool-Use for MLLMs

Xueying Jiang, Wenhao Li, Quanhao Qian +4

3D localization in Multimodal Large Language Models (MLLMs), including 3D object detection and 3D visual grounding, is fundamentally limited by camera intrinsic ambiguity: the same…

cs.CV2026

On the Generalization Capacities of MLLMs for Spatial Intelligence

Gongjie Zhang, Wenhao Li, Quanhao Qian +4

Multimodal Large Language Models (MLLMs) that directly process RGB inputs for tasks like 3D localization and navigation have shown remarkable potential. However, we argue that thes…

cs.CV2025

RoboSVG: A Unified Framework for Interactive SVG Generation with Multi-modal Guidance

Jiuniu Wang, Gongjie Zhang, Quanhao Qian +3

Scalable Vector Graphics (SVGs) are fundamental to digital design and robot control, encoding not only visual structure but also motion paths in interactive drawings. In this work,…

cs.CV2025

Towards Scalable Spatial Intelligence via 2D-to-3D Data Lifting

Xingyu Miao, Haoran Duan, Quanhao Qian +6

Spatial intelligence is emerging as a transformative frontier in AI, yet it remains constrained by the scarcity of large-scale 3D datasets. Unlike the abundant 2D imagery, acquirin…