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Diffusion Models are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Md Manjurul Ahsan , Shivakumar Raman , Yingtao Liu , Zahed Siddique

Text-to-image generative models have made remarkable advancements in generating high-quality images. However, generated images often contain undesirable artifacts or other errors due to model limitations. Existing techniques to fine-tune…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Peyman Gholami , Robert Xiao

Large-scale diffusion-based generative models have led to breakthroughs in text-conditioned high-resolution image synthesis. Starting from random noise, such text-to-image diffusion models gradually synthesize images in an iterative fashion…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Yogesh Balaji , Seungjun Nah , Xun Huang , Arash Vahdat , Jiaming Song , Qinsheng Zhang , Karsten Kreis , Miika Aittala , Timo Aila , Samuli Laine , Bryan Catanzaro , Tero Karras , Ming-Yu Liu

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided image editing. While text guidance is an intuitive editing…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Jooyoung Choi , Yunjey Choi , Yunji Kim , Junho Kim , Sungroh Yoon

We seek to give users precise control over diffusion-based image generation by modeling complex scenes as sequences of layers, which define the desired spatial arrangement and visual attributes of objects in the scene. Collage Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Vishnu Sarukkai , Linden Li , Arden Ma , Christopher Ré , Kayvon Fatahalian

Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Songwei Ge , Taesung Park , Jun-Yan Zhu , Jia-Bin Huang

Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obtaining accurate human annotations is labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Ling Fu , Zijie Wu , Yingying Zhu , Yuliang Liu , Xiang Bai

This paper introduces a novel approach to synthesize texture to dress up a given 3D object, given a text prompt. Based on the pretrained text-to-image (T2I) diffusion model, existing methods usually employ a project-and-inpaint approach, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Yuxin Liu , Minshan Xie , Hanyuan Liu , Tien-Tsin Wong

Painting embodies a unique form of visual storytelling, where the creation process is as significant as the final artwork. Although recent advances in generative models have enabled visually compelling painting synthesis, most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Ying Jiang , Jiayin Lu , Yunuo Chen , Yumeng He , Kui Wu , Yin Yang , Chenfanfu Jiang

Novel architectures have recently improved generative image synthesis leading to excellent visual quality in various tasks. Of particular note is the field of ``AI-Art'', which has seen unprecedented growth with the emergence of powerful…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Robin Rombach , Andreas Blattmann , Björn Ommer

In human-centric content generation, the pre-trained text-to-image models struggle to produce user-wanted portrait images, which retain the identity of individuals while exhibiting diverse expressions. This paper introduces our efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Renshuai Liu , Bowen Ma , Wei Zhang , Zhipeng Hu , Changjie Fan , Tangjie Lv , Yu Ding , Xuan Cheng

Generative models such as GANs and diffusion models have demonstrated impressive image generation capabilities. Despite these successes, these systems are surprisingly poor at creating images with hands. We propose a novel training…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Yue Yang , Atith N Gandhi , Greg Turk

Material reconstruction from a photograph is a key component of 3D content creation democratization. We propose to formulate this ill-posed problem as a controlled synthesis one, leveraging the recent progress in generative deep networks.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Giuseppe Vecchio , Rosalie Martin , Arthur Roullier , Adrien Kaiser , Romain Rouffet , Valentin Deschaintre , Tamy Boubekeur

Recent advances in image editing with diffusion models have achieved impressive results, offering fine-grained control over the generation process. However, these methods are computationally intensive because of their iterative nature.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Ilia Beletskii , Andrey Kuznetsov , Aibek Alanov

Painting is one of the ways for people to express their ideas, but what if people with disabilities in hands want to paint? To tackle this challenge, we create an end-to-end solution that can generate artistic images from text descriptions.…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Qinghe Tian , Jean-Claude Franchitti

Despite impressive recent advances in text-to-image diffusion models, obtaining high-quality images often requires prompt engineering by humans who have developed expertise in using them. In this work, we present NeuroPrompts, an adaptive…

Artificial Intelligence · Computer Science 2024-04-09 Shachar Rosenman , Vasudev Lal , Phillip Howard

Animation of 2D hand-drawn sketches provides an effective medium for visual communication. However, these sketches pose challenges, particularly in handling occlusions and accurately mapping motion. While 3D animation naturally addresses…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Gaurav Rai , Ojaswa Sharma
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