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Blind face restoration methods have shown remarkable performance, particularly when trained on large-scale synthetic datasets with supervised learning. These datasets are often generated by simulating low-quality face images with a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Tianshu Kuai , Sina Honari , Igor Gilitschenski , Alex Levinshtein

Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's identity when users make large edits. We propose a one-shot…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Yuta Okuyama , Yuki Endo , Yoshihiro Kanamori

Diffusion models have shown remarkable capabilities in generating high quality and creative images conditioned on text. An interesting application of such models is structure preserving text guided image editing. Existing approaches rely on…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Hareesh Ravi , Sachin Kelkar , Midhun Harikumar , Ajinkya Kale

The class-conditional image generation based on diffusion models is renowned for generating high-quality and diverse images. However, most prior efforts focus on generating images for general categories, e.g., 1000 classes in ImageNet-1k. A…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ziying Pan , Kun Wang , Gang Li , Feihong He , Yongxuan Lai

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Diffusion model has emerged as the \emph{de-facto} model for image generation, yet the heavy training overhead hinders its broader adoption in the research community. We observe that diffusion models are commonly trained to learn all…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Jiachen Lei , Qinglong Wang , Peng Cheng , Zhongjie Ba , Zhan Qin , Zhibo Wang , Zhenguang Liu , Kui Ren

This paper presents a novel approach to improving text-guided image editing using diffusion-based models. Text-guided image editing task poses key challenge of precisly locate and edit the target semantic, and previous methods fall shorts…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yihan Hu , Jianing Peng , Yiheng Lin , Ting Liu , Xiaochao Qu , Luoqi Liu , Yao Zhao , Yunchao Wei

Natural language offers a highly intuitive interface for enabling localized fine-grained edits of 3D shapes. However, prior works face challenges in preserving global coherence while locally modifying the input 3D shape. In this work, we…

Graphics · Computer Science 2025-07-22 Etai Sella , Noam Atia , Ron Mokady , Hadar Averbuch-Elor

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets. Current video editing methods commonly require per-video fine-tuning of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Zhenghao Zhang , Zuozhuo Dai , Long Qin , Weizhi Wang

Sketch-guided image editing aims to achieve local fine-tuning of the image based on the sketch information provided by the user, while maintaining the original status of the unedited areas. Due to the high cost of acquiring human sketches,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Weihang Mao , Bo Han , Zihao Wang

Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control. Unlike direct-editing tools like Photoshop, text conditioned models require the artist to perform "prompt engineering,"…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Michelle Shu , Charles Herrmann , Richard Strong Bowen , Forrester Cole , Ramin Zabih

As text-to-image models grow increasingly powerful and complex, their burgeoning size presents a significant obstacle to widespread adoption, especially on resource-constrained devices. This paper presents a pioneering study on…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Samarth N Ramesh , Zhixue Zhao

Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models pre-trained on large-scale image-text pairs are highly…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Wenliang Zhao , Yongming Rao , Zuyan Liu , Benlin Liu , Jie Zhou , Jiwen Lu

Recent advancements in diffusion models have significantly impacted the trajectory of generative machine learning research, with many adopting the strategy of fine-tuning pre-trained models using domain-specific text-to-image datasets.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Mischa Dombrowski , Hadrien Reynaud , Johanna P. Müller , Matthew Baugh , Bernhard Kainz

Recent advances in text-to-image diffusion models have substantially improved the quality of image customization, enabling the synthesis of highly realistic images. Despite this progress, achieving fast and efficient personalization remains…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Aniket Roy , Maitreya Suin , Rama Chellappa

Recent advancements in large-scale text-to-image diffusion models have enabled many applications in image editing. However, none of these methods have been able to edit the layout of single existing images. To address this gap, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-06-23 Zhiyuan Zhang , Zhitong Huang , Jing Liao

Diffusion models have achieved remarkable results in generating high-quality, diverse, and creative images. However, when it comes to text-based image generation, they often fail to capture the intended meaning presented in the text. For…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Kota Sueyoshi , Takashi Matsubara

Image-based virtual try-on is an increasingly important task for online shopping. It aims to synthesize images of a specific person wearing a specified garment. Diffusion model-based approaches have recently become popular, as they are…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Xu Yang , Changxing Ding , Zhibin Hong , Junhao Huang , Jin Tao , Xiangmin Xu

There has been tremendous progress in large-scale text-to-image synthesis driven by diffusion models enabling versatile downstream applications such as 3D object synthesis from texts, image editing, and customized generation. We present a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Ting-Hsuan Liao , Songwei Ge , Yiran Xu , Yao-Chih Lee , Badour AlBahar , Jia-Bin Huang

Recent advances in diffusion models have introduced a new era of text-guided image manipulation, enabling users to create realistic edited images with simple textual prompts. However, there is significant concern about the potential misuse…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 June Suk Choi , Kyungmin Lee , Jongheon Jeong , Saining Xie , Jinwoo Shin , Kimin Lee