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Current image fusion methods struggle to address the composite degradations encountered in real-world imaging scenarios and lack the flexibility to accommodate user-specific requirements. In response to these challenges, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Linfeng Tang , Yeda Wang , Zhanchuan Cai , Junjun Jiang , Jiayi Ma

Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose RealCompo, a new…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Xinchen Zhang , Ling Yang , Yaqi Cai , Zhaochen Yu , Kai-Ni Wang , Jiake Xie , Ye Tian , Minkai Xu , Yong Tang , Yujiu Yang , Bin Cui

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jiatao Gu , Qingzhe Gao , Shuangfei Zhai , Baoquan Chen , Lingjie Liu , Josh Susskind

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

In recent years, significant progress has been made in the development of text-to-image generation models. However, these models still face limitations when it comes to achieving full controllability during the generation process. Often,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Salaheldin Mohamed

We present a simple, yet effective diffusion-based method for fine-grained, parametric control over light sources in an image. Existing relighting methods either rely on multiple input views to perform inverse rendering at inference time,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Nadav Magar , Amir Hertz , Eric Tabellion , Yael Pritch , Alex Rav-Acha , Ariel Shamir , Yedid Hoshen

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

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

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Guangcong Zheng , Xianpan Zhou , Xuewei Li , Zhongang Qi , Ying Shan , Xi Li

Text-to-image diffusion models exhibit remarkable generative capabilities, but lack precise control over object counts and spatial arrangements. This work introduces a two-stage system to address these compositional limitations. The first…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Jan-Hendrik Koch , Jonas Krumme , Konrad Gadzicki

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

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

Generating high-fidelity images of humans with fine-grained control over attributes such as hairstyle and clothing remains a core challenge in personalized text-to-image synthesis. While prior methods emphasize identity preservation from a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Guocheng Gordon Qian , Daniil Ostashev , Egor Nemchinov , Avihay Assouline , Sergey Tulyakov , Kuan-Chieh Jackson Wang , Kfir Aberman

Food image composition requires the use of existing dish images and background images to synthesize a natural new image, while diffusion models have made significant advancements in image generation, enabling the construction of end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Chaohua Shi , Xuan Wang , Si Shi , Xule Wang , Mingrui Zhu , Nannan Wang , Xinbo Gao

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

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

Generating realistic animated videos from static images is an important area of research in computer vision. Methods based on physical simulation and motion prediction have achieved notable advances, but they are often limited to specific…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qiang Wang , Minghua Liu , Junjun Hu , Fan Jiang , Mu Xu

Utilizing pre-trained 2D large-scale generative models, recent works are capable of generating high-quality novel views from a single in-the-wild image. However, due to the lack of information from multiple views, these works encounter…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Yunhan Yang , Yukun Huang , Xiaoyang Wu , Yuan-Chen Guo , Song-Hai Zhang , Hengshuang Zhao , Tong He , Xihui Liu

Recent progress in image generation has sparked research into controlling these models through condition signals, with various methods addressing specific challenges in conditional generation. Instead of proposing another specialized…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xirui Li , Charles Herrmann , Kelvin C. K. Chan , Yinxiao Li , Deqing Sun , Chao Ma , Ming-Hsuan Yang

Image harmonization, which involves adjusting the foreground of a composite image to attain a unified visual consistency with the background, can be conceptualized as an image-to-image translation task. Diffusion models have recently…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Pengfei Zhou , Fangxiang Feng , Xiaojie Wang