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Related papers: Control Color: Multimodal Diffusion-based Interact…

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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

Diffusion models have demonstrated their ability to generate diverse and high-quality images, sparking considerable interest in their potential for real image editing applications. However, existing diffusion-based approaches for local…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Wenjing Huang , Shikui Tu , Lei Xu

There is a rapidly growing interest in controlling consistency across multiple generated images using diffusion models. Among various methods, recent works have found that simply manipulating attention modules by concatenating features from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jiaojiao Fan , Haotian Xue , Qinsheng Zhang , Yongxin Chen

Color constancy methods often struggle to generalize across different camera sensors due to varying spectral sensitivities. We present GCC, which leverages diffusion models to inpaint color checkers into images for illumination estimation.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Chen-Wei Chang , Cheng-De Fan , Chia-Che Chang , Yi-Chen Lo , Yu-Chee Tseng , Jiun-Long Huang , Yu-Lun Liu

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the color composition while the text prompt provides control…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Jaskirat Singh , Stephen Gould , Liang Zheng

Image fusion aims to integrate complementary information from multiple input images acquired through various sources to synthesize a new fused image. Existing methods usually employ distinct constraint designs tailored to specific scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Bing Cao , Xingxin Xu , Pengfei Zhu , Qilong Wang , Qinghua Hu

Diffusion-model-based text-guided image generation has recently made astounding progress, producing fascinating results in open-domain image manipulation tasks. Few models, however, currently have complete zero-shot capabilities for both…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Sijia Li , Chen Chen , Haonan Lu

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

Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information across frames. While such approaches have led to significant…

Style transfer driven by text prompts paved a new path for creatively stylizing the images without collecting an actual style image. Despite having promising results, with text-driven stylization, the user has no control over the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Prajwal Ganugula , Y S S S Santosh Kumar , N K Sagar Reddy , Prabhath Chellingi , Avinash Thakur , Neeraj Kasera , C Shyam Anand

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

Controllable image synthesis models allow creation of diverse images based on text instructions or guidance from a reference image. Recently, denoising diffusion probabilistic models have been shown to generate more realistic imagery than…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Xihui Liu , Dong Huk Park , Samaneh Azadi , Gong Zhang , Arman Chopikyan , Yuxiao Hu , Humphrey Shi , Anna Rohrbach , Trevor Darrell

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

The project has carried out the re-optimization of image coloring in accordance with the existing Autocolorization direction model DDColor. For the experiments on the existing weights of DDColor, we found that it has limitations in some…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Yun Kai Zhuang

Fashion illustration is a crucial medium for designers to convey their creative vision and transform design concepts into tangible representations that showcase the interplay between clothing and the human body. In the context of fashion…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Alberto Baldrati , Davide Morelli , Marcella Cornia , Marco Bertini , Rita Cucchiara

State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlooked is the specific camera geometry used during image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Andrey Voynov , Amir Hertz , Moab Arar , Shlomi Fruchter , Daniel Cohen-Or

As Diffusion Models have shown promising performance, a lot of efforts have been made to improve the controllability of Diffusion Models. However, how to train Diffusion Models to have the disentangled latent spaces and how to naturally…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Wonwoong Cho , Hareesh Ravi , Midhun Harikumar , Vinh Khuc , Krishna Kumar Singh , Jingwan Lu , David I. Inouye , Ajinkya Kale

Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Shu Zhang , Ning Yu , Yihao Feng , Xinyi Yang , Yingbo Zhou , Huan Wang , Juan Carlos Niebles , Caiming Xiong , Silvio Savarese , Stefano Ermon , Yun Fu , Ran Xu
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