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Diffusion Morphs (DiM) are a recent state-of-the-art method for creating high quality face morphs; however, they require a high number of network function evaluations (NFE) to create the morphs. We propose a new DiM pipeline, Fast-DiM,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Zander W. Blasingame , Chen Liu

The ever-increasing use of synthetically generated content in different sectors of our everyday life, one for all media information, poses a strong need for deepfake detection tools in order to avoid the proliferation of altered messages.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Andrea Ciamarra , Roberto Caldelli , Federico Becattini , Lorenzo Seidenari , Alberto Del Bimbo

Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturbing imagery when provided with harmful inputs. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

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

The diffusion-based text-to-image model harbors immense potential in transferring reference style. However, current encoder-based approaches significantly impair the text controllability of text-to-image models while transferring styles. In…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Tianhao Qi , Shancheng Fang , Yanze Wu , Hongtao Xie , Jiawei Liu , Lang Chen , Qian He , Yongdong Zhang

We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input…

Computer Vision and Pattern Recognition · Computer Science 2024-08-19 Zongze Wu , Nicholas Kolkin , Jonathan Brandt , Richard Zhang , Eli Shechtman

Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, translating these abilities to fine-grained image editing…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

The rapid progress of Deepfake technology has made face swapping highly realistic, raising concerns about the malicious use of fabricated facial content. Existing methods often struggle to generalize to unseen domains due to the diverse…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Ke Sun , Shen Chen , Taiping Yao , Hong Liu , Xiaoshuai Sun , Shouhong Ding , Rongrong Ji

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Michal Geyer , Omer Bar-Tal , Shai Bagon , Tali Dekel

Given a style-reference image as the additional image condition, text-to-image diffusion models have demonstrated impressive capabilities in generating images that possess the content of text prompts while adopting the visual style of the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Lin Zhu , Xinbing Wang , Chenghu Zhou , Qinying Gu , Nanyang Ye

Advanced deepfake technologies are blurring the lines between real and fake, presenting both revolutionary opportunities and alarming threats. While it unlocks novel applications in fields like entertainment and education, its malicious use…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Qihao Shen , Jiaxing Xuan , Zhenguang Liu , Sifan Wu , Yutong Xie , Zhaoyan Ming , Yingying Jiao , kui Ren

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

Leveraging the powerful capabilities of diffusion models has yielded quite effective results in medical image segmentation tasks. However, existing methods typically transfer the original training process directly without specific…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Qilin Huang , Tianyu Lin , Zhiguang Chen , Fudan Zheng

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

The rapid progress in deep generative models has led to the creation of incredibly realistic synthetic images that are becoming increasingly difficult to distinguish from real-world data. The widespread use of Variational Models, Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Anant Mehta , Bryant McArthur , Nagarjuna Kolloju , Zhengzhong Tu

Diffusion models (DMs) have revolutionized image generation, producing high-quality images with applications spanning various fields. However, their ability to create hyper-realistic images poses significant challenges in distinguishing…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Santosh , Li Lin , Irene Amerini , Xin Wang , Shu Hu

Due to the high complexity and technical requirements of industrial production processes, surface defects will inevitably appear, which seriously affects the quality of products. Although existing lightweight detection networks are highly…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xuyi Yu

Depth information provides valuable insights into the 3D structure especially the outline of objects, which can be utilized to improve the semantic segmentation tasks. However, a naive fusion of depth information can disrupt feature and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Wei Sun , Yuan Li , Qixiang Ye , Jianbin Jiao , Yanzhao Zhou

Deepfakes pose significant security and privacy threats through malicious facial manipulations. While robust watermarking can aid in authenticity verification and source tracking, existing methods often lack the sufficient robustness…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Chen Sun , Haiyang Sun , Zhiqing Guo , Yunfeng Diao , Liejun Wang , Dan Ma , Gaobo Yang , Keqin Li

Diffusion models have attained impressive visual quality for image synthesis. However, how to interpret and manipulate the latent space of diffusion models has not been extensively explored. Prior work diffusion autoencoders encode the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Zeyu Lu , Chengyue Wu , Xinyuan Chen , Yaohui Wang , Lei Bai , Yu Qiao , Xihui Liu