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Images can be viewed as layered compositions, foreground objects over background, with potential occlusions. This layered representation enables independent editing of elements, offering greater flexibility for content creation. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jingxi Chen , Yixiao Zhang , Xiaoye Qian , Zongxia Li , Cornelia Fermuller , Caren Chen , Yiannis Aloimonos

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

Deep image generation is becoming a tool to enhance artists and designers creativity potential. In this paper, we aim at making the generation process more structured and easier to interact with. Inspired by vector graphics systems, we…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Othman Sbai , Camille Couprie , Mathieu Aubry

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

Exploring and editing colors in images is a common task in graphic design and photography. However, allowing for interactive recoloring while preserving smooth color blends in the image remains a challenging problem. We present…

Graphics · Computer Science 2017-01-18 Sharon Lin , Matthew Fisher , Angela Dai , Pat Hanrahan

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

Designers craft and edit graphic designs in a layer representation, but layer-based editing becomes impossible once composited into a raster image. In this work, we propose LayerD, a method to decompose raster graphic designs into layers…

Graphics · Computer Science 2025-09-30 Tomoyuki Suzuki , Kang-Jun Liu , Naoto Inoue , Kota Yamaguchi

Recent diffusion-based approaches have made substantial progress in image layer decomposition. However, accurately decomposing complex natural images remains challenging due to difficulties in occlusion completion, robust layer…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Binhao Wang , Shihao Zhao , Bo Cheng , Qiuyu Ji , Yuhang Ma , Liebucha Wu , Shanyuan Liu , Dawei Leng , Yuhui Yin

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

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

Given a video and a set of input object masks, an omnimatte method aims to decompose the video into semantically meaningful layers containing individual objects along with their associated effects, such as shadows and reflections. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yao-Chih Lee , Erika Lu , Sarah Rumbley , Michal Geyer , Jia-Bin Huang , Tali Dekel , Forrester Cole

Despite their impressive visual fidelity, existing personalized image generators lack interactive control over spatial composition and scale poorly to multiple humans. To address these limitations, we present LayerComposer, an interactive…

Recent visual generative models often struggle with consistency during image editing due to the entangled nature of raster images, where all visual content is fused into a single canvas. In contrast, professional design tools employ layered…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Shengming Yin , Zekai Zhang , Zecheng Tang , Kaiyuan Gao , Xiao Xu , Kun Yan , Jiahao Li , Yilei Chen , Yuxiang Chen , Heung-Yeung Shum , Lionel M. Ni , Jingren Zhou , Junyang Lin , Chenfei Wu

Disentangling visual layers in real-world images is a persistent challenge in vision and graphics, as such layers often involve non-linear and globally coupled interactions, including shading, reflection, and perspective distortion. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Zheng Gu , Min Lu , Zhida Sun , Dani Lischinski , Daniel Cohen-Or , Hui Huang

We show how to extend traditional intrinsic image decompositions to incorporate further layers above albedo and shading. It is hard to obtain data to learn a multi-layer decomposition. Instead, we can learn to decompose an image into layers…

Computer Vision and Pattern Recognition · Computer Science 2016-12-06 Jason Rock , Theerasit Issaranon , Aditya Deshpande , David Forsyth

Large-scale generative models have achieved remarkable advancements in various visual tasks, yet their application to shadow removal in images remains challenging. These models often generate diverse, realistic details without adequate…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Xinjie Li , Yang Zhao , Dong Wang , Yuan Chen , Li Cao , Xiaoping Liu

Tremendous progress in deep generative models has led to photorealistic image synthesis. While achieving compelling results, most approaches operate in the two-dimensional image domain, ignoring the three-dimensional nature of our world.…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Michael Niemeyer , Andreas Geiger

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 spatial-aware image editing abilities into one framework, we…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yueru Jia , Yuhui Yuan , Aosong Cheng , Chuke Wang , Ji Li , Huizhu Jia , Shanghang Zhang

Radiance fields have gradually become a main representation of media. Although its appearance editing has been studied, how to achieve view-consistent recoloring in an efficient manner is still under explored. We present RecolorNeRF, a…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Bingchen Gong , Yuehao Wang , Xiaoguang Han , Qi Dou

Photographers routinely compose multiple manipulated photos of the same scene (layers) into a single image, which is better than any individual photo could be alone. Similarly, 3D artists set up rendering systems to produce layered images…

Graphics · Computer Science 2017-02-03 Carlo Innamorati , Tobias Ritschel , Tim Weyrich , Niloy J. Mitra
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