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Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed images. However, they failed to capture critical…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Yufei Wang , Yi Yu , Wenhan Yang , Lanqing Guo , Lap-Pui Chau , Alex C. Kot , Bihan Wen

We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

Group portrait editing is highly desirable since users constantly want to add a person, delete a person, or manipulate existing persons. It is also challenging due to the intricate dynamics of human interactions and the diverse gestures. In…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Yuming Jiang , Nanxuan Zhao , Qing Liu , Krishna Kumar Singh , Shuai Yang , Chen Change Loy , Ziwei Liu

Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field of Artificial Intelligence Generative Content (AIGC).…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Xincheng Shuai , Henghui Ding , Xingjun Ma , Rongcheng Tu , Yu-Gang Jiang , Dacheng Tao

The pose-guided person image generation task requires synthesizing photorealistic images of humans in arbitrary poses. The existing approaches use generative adversarial networks that do not necessarily maintain realistic textures or need…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Ankan Kumar Bhunia , Salman Khan , Hisham Cholakkal , Rao Muhammad Anwer , Jorma Laaksonen , Mubarak Shah , Fahad Shahbaz Khan

Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques, such as MultiDiffusion and SyncDiffusion, have further…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Stanislav Frolov , Brian B. Moser , Andreas Dengel

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

Recent advances in diffusion-based generative models have shown incredible promise for zero shot image-to-image translation and editing. Most of these approaches work by combining or replacing network-specific features used in the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Zeqi Gu , Ethan Yang , Abe Davis

Three-dimensional microscopy is often limited by anisotropic spatial resolution, resulting in lower axial resolution than lateral resolution. Current State-of-The-Art (SoTA) isotropic reconstruction methods utilizing deep neural networks…

Image and Video Processing · Electrical Eng. & Systems 2023-06-22 Mingjie Pan , Yulu Gan , Fangxu Zhou , Jiaming Liu , Aimin Wang , Shanghang Zhang , Dawei Li

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

While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains challenging, particularly in maintaining multi-view consistency. Classical approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufeng Chi , Huimin Ma , Kafeng Wang , Jianmin Li

Standard diffusion models involve an image transform -- adding Gaussian noise -- and an image restoration operator that inverts this degradation. We observe that the generative behavior of diffusion models is not strongly dependent on the…

Computer Vision and Pattern Recognition · Computer Science 2022-08-22 Arpit Bansal , Eitan Borgnia , Hong-Min Chu , Jie S. Li , Hamid Kazemi , Furong Huang , Micah Goldblum , Jonas Geiping , Tom Goldstein

Low-light image enhancement aims to improve the visibility of degraded images to better align with human visual perception. While diffusion-based methods have shown promising performance due to their strong generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Jinhong He , Minglong Xue , Zhipu Liu , Mingliang Zhou , Aoxiang Ning , Palaiahnakote Shivakumara

Video Motion Magnification (VMM) amplifies subtle macroscopic motions to a perceptible level. Recently, existing mainstream Eulerian approaches address amplification-induced noise via decoupling representation learning such as texture,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Xuedeng Liu , Jiabao Guo , Zheng Zhang , Fei Wang , Zhi Liu , Dan Guo

Diffusion models dominate image editing, yet their global denoising mechanism entangles edited regions with surrounding context, causing modifications to propagate into areas that should remain intact. We propose a fundamentally different…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Wei Chow , Linfeng Li , Xian Sun , Lingdong Kong , Zefeng Li , Qi Xu , Hang Song , Tian Ye , Xian Wang , Jinbin Bai , Shilin Xu , Xiangtai Li , Junting Pan , Shaoteng Liu , Ran Zhou , Tianshu Yang , Songhua Liu

We present the first text-based image editing approach for object parts based on pre-trained diffusion models. Diffusion-based image editing approaches capitalized on the deep understanding of diffusion models of image semantics to perform…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Aleksandar Cvejic , Abdelrahman Eldesokey , Peter Wonka

When using a diffusion model for image editing, there are times when the modified image can differ greatly from the source. To address this, we apply a dual-guidance approach to maintain high fidelity to the original in areas that are not…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Ruichen Zhang

Accurate completion and denoising of roof height maps are crucial to reconstructing high-quality 3D buildings. Repairing sparse points can enhance low-cost sensor use and reduce UAV flight overlap. RoofDiffusion is a new end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Kyle Shih-Huang Lo , Jörg Peters , Eric Spellman

Scene text editing is a challenging task that involves modifying or inserting specified texts in an image while maintaining its natural and realistic appearance. Most previous approaches to this task rely on style-transfer models that crop…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Jiabao Ji , Guanhua Zhang , Zhaowen Wang , Bairu Hou , Zhifei Zhang , Brian Price , Shiyu Chang

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical images (whether focused by lenses or not) are diffraction…

Optics · Physics 2021-04-08 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta
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