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Shizhao Sun

12 accepted papers

2026

Can Vision–Language Models Assess Graphic Design Aesthetics? A Benchmark, Evaluation, and Dataset Perspective.

ICLR 2026poster

Assessing the aesthetic quality of graphic design is central to visual communication, yet remains underexplored in vision–language models (VLMs). We investigate whether VLMs can evaluate design aesthetics in ways comparable to humans. Prior work faces three key limitations: benchmarks restricted to…

Cited by 0SourcecodeScholar
2026

Orchestrating Spatial Semantics via a Zone-Graph Paradigm for Intricate Indoor Scene Generation

ICML 2026poster

Autonomous 3D indoor scene synthesis breaks down in non-convex rooms with tightly coupled spatial constraints. Data-driven generators lack topological priors for long-horizon planning, while iterative agents fragment semantics and become geometrically brittle. We present \textbf{ZoneMaestro}, a unif…

Cited by 0SourceScholar
2025

CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing

ICML 2025poster

Computer Aided Design (CAD) is indispensable across various industries. \emph{Text-based CAD editing}, which automates the modification of CAD models based on textual instructions, holds great potential but remains underexplored. Existing methods primarily focus on design variation generation or te…

Cited by 0SourcePDFScholar
2025

CADMorph: Geometry‑Driven Parametric CAD Editing via a Plan–Generate–Verify Loop

NeurIPS 2025poster

A Computer-Aided Design (CAD) model encodes an object in two coupled forms: a \emph{parametric construction sequence} and its resulting \emph{visible geometric shape}. During iterative design, adjustments to the geometric shape inevitably require synchronized edits to the underlying parametric seque…

Cited by 0SourceScholar
2025

FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models

ICLR 2025poster

Recently, there is a growing interest in creating computer-aided design (CAD) models based on user intent, known as controllable CAD generation. Existing work offers limited controllability and needs separate models for different types of control, reducing efficiency and practicality. To achieve con…

2025

Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models

ICML 2025poster

Creating Computer-Aided Design (CAD) models requires significant expertise and effort. Text-to-CAD, which converts textual descriptions into CAD parametric sequences, is crucial in streamlining this process. Recent studies have utilized ground-truth parametric sequences, known as sequential signals…

Cited by 1SourcePDFScholar
2023

A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptions

ICCV 2023poster

Creating layouts is a fundamental step in graphic design. In this work, we propose to use text as the guidance to create graphic layouts, i.e., Text-to-Layout, aiming to lower the design barriers. Text-to-Layout is a challenging task, because it needs to consider the implicit, combined, and incomple…

Cited by 12PDFScholar
2023

LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models

ICCV 2023poster

Creating graphic layouts is a fundamental step in graphic designs. In this work, we present a novel generative model named LayoutDiffusion for automatic layout generation. As layout is typically represented as a sequence of discrete tokens, LayoutDiffusion models layout generation as a discrete deno…

Cited by 50PDFcodeScholar
2023

LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restriction

CVPR 2023poster

Conditional graphic layout generation, which generates realistic layouts according to user constraints, is a challenging task that has not been well-studied yet. First, there is limited discussion about how to handle diverse user constraints flexibly and uniformly. Second, to make the layouts confor…

Cited by 44SourcePDFScholar
2023

LayoutPrompter: Awaken the Design Ability of Large Language Models

NeurIPS 2023poster

Conditional graphic layout generation, which automatically maps user constraints to high-quality layouts, has attracted widespread attention today. Although recent works have achieved promising performance, the lack of versatility and data efficiency hinders their practical applications. In this wor…

2022

Coarse-to-Fine Generative Modeling for Graphic Layouts

AAAI 2022technical

Even though graphic layout generation has attracted growing attention recently, it is still challenging to synthesis realistic and diverse layouts, due to the complicated element relationships and varied element arrangements. In this work, we seek to improve the performance of layout generation by i…

Cited by 43SourcePDFScholar