paper-with-me

홈 › Papers

ChatPattern: Layout Pattern Customization via Natural Language

2024-03-15 · Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu

Existing works focus on fixed-size layout pattern generation, while the more practical free-size pattern generation receives limited attention. In this paper, we propose ChatPattern, a novel Large-Language-Model (LLM) powered framework for flexible pattern customization. ChatPattern utilizes a two-part system featuring an expert LLM agent and a highly controllable layout pattern generator. The LLM agent can interpret natural language requirements and operate design tools to meet specified needs, while the generator excels in conditional layout generation, pattern modification, and memory-friendly patterns extension. Experiments on challenging pattern generation setting shows the ability of ChatPattern to synthesize high-quality large-scale patterns.

📄 PDF Abstract BibTeX arXiv:2403.15434

Code (0)

등록된 구현이 없습니다.

Tasks

Language ModelingLanguage ModellingLarge Language ModelLayout Generation

Methods 이 논문이 사용한 방법론

Focus 설명 없음

Similar Papers 제목 키워드 기반

UniSparse: An Intermediate Language for General Sparse Format Customization

2024-03-09 · Jie Liu, Zhongyuan Zhao, Zijian Ding, Benjamin Brock 외

The ongoing trend of hardware specialization has led to a growing use of custom data formats when processing sparse workloads, which are typically memory-bound. These formats facilitate optimized software/hardware implem…

AttributeCode GenerationCPUGPU

WorldCraft: Photo-Realistic 3D World Creation and Customization via LLM Agents

2025-02-21 · Xinhang Liu, Chi-Keung Tang, Yu-Wing Tai

Constructing photorealistic virtual worlds has applications across various fields, but it often requires the extensive labor of highly trained professionals to operate conventional 3D modeling software. To democratize th…

Large Language Model

GroundingBooth: Grounding Text-to-Image Customization

2024-09-13 · Zhexiao Xiong, Wei Xiong, Jing Shi, He Zhang 외

Recent studies in text-to-image customization show great success in generating personalized object variants given several images of a subject. While existing methods focus more on preserving the identity of the subject, …

Image Generation

AnyMS: Bottom-up Attention Decoupling for Layout-guided and Training-free Multi-subject Customization

2025-12-29 · Binhe Yu, Zhen Wang, Kexin Li, Yuqian Yuan 외 arxiv

Multi-subject customization aims to synthesize multiple user-specified subjects into a coherent image. To address issues such as subjects missing or conflicts, recent works incorporate layout guidance to provide explicit…

PositionIC: Unified Position and Identity Consistency for Image Customization

2025-07-18 · Junjie Hu, Tianyang Han, Kai Ma, Jialin Gao 외 arxiv

Recent subject-driven image customization excels in fidelity, yet fine-grained instance-level spatial control remains an elusive challenge, hindering real-world applications. This limitation stems from two factors: a sca…