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Text-driven image generation using diffusion models has recently gained significant attention. To enable more flexible image manipulation and editing, recent research has expanded from single image generation to transparent layer generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Junjia Huang , Pengxiang Yan , Jinhang Cai , Jiyang Liu , Zhao Wang , Yitong Wang , Xinglong Wu , Guanbin Li

We present LayerDiffuse, an approach enabling large-scale pretrained latent diffusion models to generate transparent images. The method allows generation of single transparent images or of multiple transparent layers. The method learns a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Lvmin Zhang , Maneesh Agrawala

Large-scale diffusion models have achieved remarkable success in generating high-quality images from textual descriptions, gaining popularity across various applications. However, the generation of layered content, such as transparent…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Yusuf Dalva , Yijun Li , Qing Liu , Nanxuan Zhao , Jianming Zhang , Zhe Lin , Pinar Yanardag

Transparent image layer generation plays a significant role in digital art and design workflows. Existing methods typically decompose transparent layers from a single RGB image using a set of tools or generate multiple transparent layers…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Dingbang Huang , Wenbo Li , Yifei Zhao , Xinyu Pan , Chun Wang , Yanhong Zeng , Bo Dai

Multi-layer image generation is a fundamental task that enables users to isolate, select, and edit specific image layers, thereby revolutionizing interactions with generative models. In this paper, we introduce the Anonymous Region…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Yifan Pu , Yiming Zhao , Zhicong Tang , Ruihong Yin , Haoxing Ye , Yuhui Yuan , Dong Chen , Jianmin Bao , Sirui Zhang , Yanbin Wang , Lin Liang , Lijuan Wang , Ji Li , Xiu Li , Zhouhui Lian , Gao Huang , Baining Guo

Recent advancements in large generative models, particularly diffusion-based methods, have significantly enhanced the capabilities of image editing. However, achieving precise control over image composition tasks remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Jinrui Yang , Qing Liu , Yijun Li , Soo Ye Kim , Daniil Pakhomov , Mengwei Ren , Jianming Zhang , Zhe Lin , Cihang Xie , Yuyin Zhou

Transparent objects are common in daily life, and understanding their multi-layer depth information -- perceiving both the transparent surface and the objects behind it -- is crucial for real-world applications that interact with…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Hongyu Wen , Yiming Zuo , Venkat Subramanian , Patrick Chen , Jia Deng

Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provide object-wise manipulation capability. To support wider…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Runhui Huang , Kaixin Cai , Jianhua Han , Xiaodan Liang , Renjing Pei , Guansong Lu , Songcen Xu , Wei Zhang , Hang Xu

Layered image generation and editing is a fundamental capability that enables layer-wise reuse, editing, and composition of generated visual content, analogous to word-level editing in natural language. Despite its importance, this remains…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Zhicong Tang , Zhao Zhang , Jingye Chen , Mohan Zhou , Yifan Pu , Yuchi Liu , Yalong Bai , Ethan Smith , Yuhui Yuan

Despite recent advances in deep generative modeling, skin lesion classification systems remain constrained by the limited availability of large, diverse, and well-annotated clinical datasets, resulting in class imbalance between benign and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Stathis Galanakis , Alexandros Koliousis , Stefanos Zafeiriou

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances in layered image generation and decomposition synthesize or recover layered…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Ryugo Morita , Stanislav Frolov , Brian Bernhard Moser , Ko Watanabe , Riku Takahashi , Issey Sukeda , Andreas Dengel

Layers have become indispensable tools for professional artists, allowing them to build a hierarchical structure that enables independent control over individual visual elements. In this paper, we propose LayeringDiff, a novel pipeline for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Kyoungkook Kang , Gyujin Sim , Geonung Kim , Donguk Kim , Seungho Nam , Sunghyun Cho

Recent advances in image generation have made it easy to produce high-quality images. However, these outputs are inherently flattened, entangling foreground elements, background, and text within a fixed canvas. As a result, flexible…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Kam Man Wu , Haolin Yang , Qingyu Chen , Yihu Tang , Jingye Chen , Qifeng Chen

Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex prompts, such as those that involve numeracy and spatial…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Long Lian , Boyi Li , Adam Yala , Trevor Darrell

In controllable generation tasks, flexibly manipulating the generated images to attain a desired appearance or structure based on a single input image cue remains a critical and longstanding challenge. Achieving this requires the effective…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Xi Wang , Yichen Peng , Heng Fang , Yilin Wang , Haoran Xie , Xi Yang , Chuntao Li

Layer compositing is one of the most popular image editing workflows among both amateurs and professionals. Motivated by the success of diffusion models, we explore layer compositing from a layered image generation perspective. Instead of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Xinyang Zhang , Wentian Zhao , Xin Lu , Jeff Chien

As generative models expand the possibilities of visual content creation, layered image synthesis has emerged as a promising direction for controllable and creative editing. However, existing methods struggle to fully realize this…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Kyoungkook Kang , Gyujin Sim , Sunghyun Cho

Text-to-image (T2I) diffusion/flow models have drawn considerable attention recently due to their remarkable ability to deliver flexible visual creations. Still, high-resolution image synthesis presents formidable challenges due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jiazi Bu , Pengyang Ling , Yujie Zhou , Pan Zhang , Tong Wu , Xiaoyi Dong , Yuhang Zang , Yuhang Cao , Dahua Lin , Jiaqi Wang

Image tiling -- the seamless connection of disparate images to create a coherent visual field -- is crucial for applications such as texture creation, video game asset development, and digital art. Traditionally, tiles have been constructed…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Or Madar , Ohad Fried
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