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Ruifeng Luo

4 accepted papers

2025

ArchCAD-400K: A Large-Scale CAD drawings Dataset and New Baseline for Panoptic Symbol Spotting

NeurIPS 2025poster

Recognizing symbols in architectural CAD drawings is critical for various advanced engineering applications. In this paper, we propose a novel CAD data annotation engine that leverages intrinsic attributes from systematically archived CAD drawings to automatically generate high-quality annotations,…

Cited by 0SourceScholar
2025

Point or Line? Using Line-based Representation for Panoptic Symbol Spotting in CAD Drawings

NeurIPS 2025poster

We study the task of panoptic symbol spotting, which involves identifying both individual instances of countable \textit{things} and the semantic regions of uncountable \textit{stuff} in computer-aided design (CAD) drawings composed of vector graphical primitives. Existing methods typically rely on…

Cited by 0SourceScholar
2024

StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer

COLING 2024main

Unsupervised text style transfer aims to modify the style of a sentence while preserving its content without parallel corpora. Existing approaches attempt to separate content from style, but some words contain both content and style information. It makes them difficult to disentangle, where unsatisf…

Cited by 3SourcePDFScholar
2023

Automatic Truss Design with Reinforcement Learning

IJCAI 2023poster

Truss layout design, namely finding a lightweight truss layout satisfying all the physical constraints, is a fundamental problem in the building industry. Generating the optimal layout is a challenging combinatorial optimization problem, which can be extremely expensive to solve by exhaustive search…