Xuran He

2 accepted papers

2026

Audio-2-Shape: 3D Generation from What You Hear

ICRA 2026poster

Audio serves as an important bridge connecting humans to their surroundings, providing a unique modality for perceiving the world. For embodied AI systems, such as robots and autonomous vehicles, enabling them to understand the world through sound is a promising and significant research direction. I…

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2026

UM3D: Towards a Unified Multimodal 3D Shape Generation Model

Xian-Feng Han, Zecheng Zhang, Xuran He, Ming-Jie Wang

ICRA 2026poster

Vision-Language Pre-training models (VLMs) have emerged as a highly promising solution to the generative problem, achieving remarkable success in the field of 2D image generation. However, extending these 2D paradigms to 3D domains is still unexplored due to the scarcity of text-3D pairs and shape a…

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