Qihong Tang — accepted AI-conference papers

2026

Prompt-Free Universal Region Proposal Network

Qihong Tang, Changhan Liu, Shaofeng Zhang, Wenbin Li, Qi Fan, Yang Gao

CVPR 2026

Identifying potential objects is critical for object recognition and analysis across various computer vision applications. Existing methods typically localize potential objects by relying on exemplar images, predefined categories, or textual descriptions. However, their reliance on image and text pr

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2025

MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds

BingQuan Dai, Luo Li, Qihong Tang, Jie Wang, Xinyu Lian, Hao Xu +6

NeurIPS 2025poster

Reconstructing 3D objects into editable programs is pivotal for applications like reverse engineering and shape editing. However, existing methods often rely on limited domain-specific languages (DSLs) and small-scale datasets, restricting their ability to model complex geometries and structures. To…

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