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A multi-layer image is more valuable than a single-layer image from a graphic designer's perspective. However, most of the proposed image generation methods so far focus on single-layer images. In this paper, we propose MontageGAN, which is…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Chean Fei Shee , Seiichi Uchida

This paper presents a novel deep learning-based approach for automatically vectorizing and synthesizing the clipart of man-made objects. Given a raster clipart image and its corresponding object category (e.g., airplanes), the proposed…

Graphics · Computer Science 2021-06-10 I-Chao Shen , Bing-Yu Chen

Text-to-image diffusion models can synthesize high-quality images, but they have various limitations. Here we highlight a common failure mode of these models, namely, generating uncommon concepts and structured concepts like hand palms. We…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Dvir Samuel , Rami Ben-Ari , Simon Raviv , Nir Darshan , Gal Chechik

Depth-of-field control is essential in photography, but achieving perfect focus often requires multiple attempts or specialized equipment. Single-image refocusing is still difficult. It involves recovering sharp content and creating…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Chun-Wei Tuan Mu , Cheng-De Fan , Jia-Bin Huang , Yu-Lun Liu

In this paper we investigate image generation guided by hand sketch. When the input sketch is badly drawn, the output of common image-to-image translation follows the input edges due to the hard condition imposed by the translation process.…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Yongyi Lu , Shangzhe Wu , Yu-Wing Tai , Chi-Keung Tang

Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling static editing and dynamic generation, while also struggling…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Ruisi Zhao , Zechuan Zhang , Zongxin Yang , Yi Yang

Generative adversarial networks (GANs) can now generate photo-realistic images. However, how to best control the image content remains an open challenge. We introduce LatentKeypointGAN, a two-stage GAN internally conditioned on a set of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-10 Xingzhe He , Bastian Wandt , Helge Rhodin

In order to operate autonomously, a robot should explore the environment and build a model of each of the surrounding objects. A common approach is to carefully scan the whole workspace. This is time-consuming. It is also often impossible…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Karol Piaskowski , Rafal Staszak , Dominik Belter

Outfit generation is a challenging task in the field of fashion technology, in which the aim is to create a collocated set of fashion items that complement a given set of items. Previous studies in this area have been limited to generating…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Dongliang Zhou , Haijun Zhang , Jianghong Ma , Jicong Fan , Zhao Zhang

Image and texture synthesis is a challenging task that has long been drawing attention in the fields of image processing, graphics, and machine learning. This problem consists of modelling the desired type of images, either through training…

Computer Vision and Pattern Recognition · Computer Science 2016-09-26 Yi Ren , Yaniv Romano , Michael Elad

Recent remarkable improvements in large-scale text-to-image generative models have shown promising results in generating high-fidelity images. To further enhance editability and enable fine-grained generation, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Kangyeol Kim , Sunghyun Park , Junsoo Lee , Jaegul Choo

Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Álvaro Barbero Jiménez

Affine transformation, layer blending, and artistic filters are popular processes that graphic designers employ to transform pixels of an image to create a desired effect. Here, we examine various approaches that synthesize new images:…

Graphics · Computer Science 2019-01-16 Somnuk Phon-Amnuaisuk

Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind. If this new technology is to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Marek Kowalski , Stephan J. Garbin , Virginia Estellers , Tadas Baltrušaitis , Matthew Johnson , Jamie Shotton

This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engineering design synthesis. Our model proposes parametric,…

Artificial Intelligence · Computer Science 2024-12-09 Rui Zhou , Yanxia Zhang , Chenyang Yuan , Frank Permenter , Nikos Arechiga , Matt Klenk , Faez Ahmed

Image inpainting aims to restore the missing regions of corrupted images and make the recovery result identical to the originally complete image, which is different from the common generative task emphasizing the naturalness or realism of…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Qing Guo , Xiaoguang Li , Felix Juefei-Xu , Hongkai Yu , Yang Liu , Song wang

Generative diffusion models offer a natural choice for data augmentation when training complex vision models. However, ensuring reliability of their generative content as augmentation samples remains an open challenge. Despite a number of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Khawar Islam , Naveed Akhtar

The process of painting fosters creativity and rational planning. However, existing generative AI mostly focuses on producing visually pleasant artworks, without emphasizing the painting process. We introduce a novel task, Collaborative…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Nicola Dall'Asen , Willi Menapace , Elia Peruzzo , Enver Sangineto , Yiming Wang , Elisa Ricci

To truly understand the visual world our models should be able not only to recognize images but also generate them. To this end, there has been exciting recent progress on generating images from natural language descriptions. These methods…

Computer Vision and Pattern Recognition · Computer Science 2018-04-06 Justin Johnson , Agrim Gupta , Li Fei-Fei

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein
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