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Chin-Yi Cheng

10 accepted papers

2023

PLay: Parametrically Conditioned Layout Generation using Latent Diffusion

ICML 2023poster

Layout design is an important task in various design fields, including user interfaces, document, and graphic design. As this task requires tedious manual effort by designers, prior works have attempted to automate this process using generative models, but commonly fell short of providing intuitive…

Cited by 31SourcePDFScholar
2022

CLIP-Forge: Towards Zero-Shot Text-To-Shape Generation

CVPR 2022poster

Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent progress has been made in text-to-image generation, text-to-shape generation remains a challenging problem due to the unavailability of paired text and shape data at…

Cited by 323PDFcodeScholar
2022

IKEA-Manual: Seeing Shape Assembly Step by Step

NeurIPS 2022accept

Human-designed visual manuals are crucial components in shape assembly activities. They provide step-by-step guidance on how we should move and connect different parts in a convenient and physically-realizable way. While there has been an ongoing effort in building agents that perform assembly tasks…

Cited by 19SourcePDFScholar
2022

SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks

ICML 2022spotlight

We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model utilizes distinct Transformer architectures to encode topological, geometric, and extrusion variations of construction seque…

2022

Translating a Visual LEGO Manual to a Machine-Executable Plan

ECCV 2022poster

"We study the problem of translating an image-based, step-by-step assembly manual created by human designers into machine-interpretable instructions. We formulate this problem as a sequential prediction task: at each step, our model reads the manual, locates the components to be added to the current…

Cited by 22SourcePDFScholar
2021

Building-GAN: Graph-Conditioned Architectural Volumetric Design Generation

ICCV 2021poster

Volumetric design is the first and critical step for professional building design, where architects not only depict the rough 3D geometry of the building but also specify the programs to form a 2D layout on each floor. Though 2D layout generation for a single story has been widely studied, there is…

Cited by 62PDFScholar
2021

House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects

CVPR 2021poster

This paper proposes a generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relational GAN and a conditional GAN, where a previously generated layout becomes the next input constraint, enabling iterative refinem…

Cited by 212PDFcodeScholar
2021

Inferring CAD Modeling Sequences Using Zone Graphs

CVPR 2021poster

In computer-aided design (CAD), the ability to "reverse engineer" the modeling steps used to create 3D shapes is a long-sought-after goal. This process can be decomposed into two sub-problems: converting an input mesh or point cloud into a boundary representation (or B-rep), and then inferring model…

Cited by 75PDFcodeScholar
2020

House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation

ECCV 2020poster

This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture. The main idea is to encode the constraint into the graph structure of its relational networks. We have demonstrated the proposed architecture for a…

Cited by 359SourcePDFScholar