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Yongkang Dai

3 accepted papers

2026

AutoRegressive Generation with B-rep Holistic Token Sequence Representation

CVPR 2026

Previous representation and generation approaches for the B-rep relied on graph-based representations that disentangle geometric and topological features through decoupled computational pipelines, thereby precluding the application of sequence-based generative frameworks, such as transformer archite

Cited by 0SourcecodeScholar
2026

BrepVGAE: Variational Graph Autoencoder with Unified Latent Representation for B-rep

CVPR 2026

Due to the heterogeneity of faces and edges in B-rep, conventional graph-based representations is incapable of establishing a unified formulation for faces and edges, thereby constraining the capabilities of B-rep generative models. We propose a B-rep Variational Graph Auto Encoding (BrepVGAE), the

Cited by 0SourceScholar
2025

MamTiff-CAD: Multi-Scale Latent Diffusion with Mamba+ for Complex Parametric Sequence

ICCV 2025poster

Parametric Computer-Aided Design (CAD) is crucial in industrial applications, yet existing approaches often struggle to generate long sequence parametric commands due to complex CAD models' geometric and topological constraints. To address this challenge, we propose MamTiff-CAD, a novel CAD parametr…

Cited by 0SourcePDFScholar