BingQuan Dai — accepted AI-conference papers

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…

Cited by 0 Source ↗Scholar ↗

2022

Boosting Supervised Dehazing Methods via Bi-Level Patch Reweighting

Xingyu Jiang, Hongkun Dou, Chengwei Fu, Bingquan Dai, Tianrun Xu, Yue Deng

ECCV 2022poster

"Natural images can suffer from non-uniform haze distributions in different regions. However, this important fact is hardly considered in existing supervised dehazing methods, in which all training patches are accounted for equally in the loss design. These supervised methods may fail in making prom…

Cited by 8 Source ↗PDF ↗Scholar ↗