1 citations · 1 across the 14 of their papers we have counts for
15 papers
PixelART: Image-to-Layer Decomposition without Latents or Text-to-Image Pretraining
Zelin Jia, Zhao Zhang, Zhicong Tang +2
Image-to-layer decomposition converts a flattened image into editable RGBA layers, enabling element-level editing in design workflows. Existing diffusion-based systems typically ad…
Detect Anything in Graphic Design: Element-Level Rewards for Autoregressive Detection
Jiangning Zhu, Bowen Li, Shenyu Qiao +4
Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating information and shaping understanding. Unlike natural images, they con…
Demystifying Numerosity in Diffusion Models -- Limitations and Remedies
Yaqi Zhao, Xiaochen Wang, Li Dong +2
Numerosity remains a challenge for state-of-the-art text-to-image generation models like FLUX and GPT-4o, which often fail to accurately follow counting instructions in text prompt…
MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoning
Yuxuan Luo, Yuhui Yuan, Junwen Chen +6
In this paper, we introduce knowledge image generation as a new task, alongside the Massive Multi-Discipline Multi-Tier Knowledge-Image Generation Benchmark (MMMG) to probe the rea…
PrismLayers: Open Data for High-Quality Multi-Layer Transparent Image Generative Models
Junwen Chen, Heyang Jiang, Yanbin Wang +6
Generating high-quality, multi-layer transparent images from text prompts can unlock a new level of creative control, allowing users to edit each layer as effortlessly as editing t…
InfoDet: A Dataset for Infographic Element Detection
Jiangning Zhu, Yuxing Zhou, Zheng Wang +4
Given the central role of charts in scientific, business, and communication contexts, enhancing the chart understanding capabilities of vision-language models (VLMs) has become inc…
BizGen: Advancing Article-level Visual Text Rendering for Infographics Generation
Yuyang Peng, Shishi Xiao, Keming Wu +6
Recently, state-of-the-art text-to-image generation models, such as Flux and Ideogram 2.0, have made significant progress in sentence-level visual text rendering. In this paper, we…
ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation
Yifan Pu, Yiming Zhao, Zhicong Tang +14
Multi-layer image generation is a fundamental task that enables users to isolate, select, and edit specific image layers, thereby revolutionizing interactions with generative model…
Efficient Diffusion Transformer with Step-wise Dynamic Attention Mediators
Yifan Pu, Zhuofan Xia, Jiayi Guo +9
This paper identifies significant redundancy in the query-key interactions within self-attention mechanisms of diffusion transformer models, particularly during the early stages of…
Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Multilingual Visual Text Rendering
Zeyu Liu, Weicong Liang, Yiming Zhao +5
Recently, Glyph-ByT5 has achieved highly accurate visual text rendering performance in graphic design images. However, it still focuses solely on English and performs relatively po…
FontStudio: Shape-Adaptive Diffusion Model for Coherent and Consistent Font Effect Generation
Xinzhi Mu, Li Chen, Bohan Chen +5
Recently, the application of modern diffusion-based text-to-image generation models for creating artistic fonts, traditionally the domain of professional designers, has garnered si…
Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization
Zhanhao Liang, Yuhui Yuan, Shuyang Gu +5
Generating visually appealing images is fundamental to modern text-to-image generation models. A potential solution to better aesthetics is direct preference optimization (DPO), wh…
DesignEdit: Multi-Layered Latent Decomposition and Fusion for Unified & Accurate Image Editing
Yueru Jia, Yuhui Yuan, Aosong Cheng +4
Recently, how to achieve precise image editing has attracted increasing attention, especially given the remarkable success of text-to-image generation models. To unify various spat…
High-Quality 3D Creation from A Single Image Using Subject-Specific Knowledge Prior
Nan Huang, Ting Zhang, Yuhui Yuan +2
In this paper, we address the critical bottleneck in robotics caused by the scarcity of diverse 3D data by presenting a novel two-stage approach for generating high-quality 3D mode…
COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design
Peidong Jia, Chenxuan Li, Yuhui Yuan +10
Graphic design, which has been evolving since the 15th century, plays a crucial role in advertising. The creation of high-quality designs demands design-oriented planning, reasonin…