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Related papers: Gaussian highpass guided image filtering

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Collaborative filtering is a critical technique in recommender systems. It has been increasingly viewed as a conditional generative task for user feedback data, where newly developed diffusion model shows great potential. However, existing…

Information Retrieval · Computer Science 2024-04-25 Yunqin Zhu , Chao Wang , Qi Zhang , Hui Xiong

3D Gaussian Splatting (3DGS) enables photorealistic rendering but suffers from artefacts due to sparse Structure-from-Motion (SfM) initialisation. To address this limitation, we propose GP-GS, a Gaussian Process (GP) based densification…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Zhihao Guo , Jingxuan Su , Chenghao Qian , Shenglin Wang , Jinlong Fan , Jing Zhang , Wei Zhou , Hadi Amirpour , Yunlong Zhao , Liangxiu Han , Peng Wang

Deep learning-based methods have achieved significant performance for image defogging. However, existing methods are mainly developed for land scenes and perform poorly when dealing with overwater foggy images, since overwater scenes…

Computer Vision and Pattern Recognition · Computer Science 2022-12-26 Yaozong Mo , Chaofeng Li , Wenqi Ren , Shaopeng Shang , Wenwu Wang , Xiao-jun Wu

An unfocused plenoptic light field (LF) camera places an array of microlenses in front of an image sensor in order to separately capture different directional rays arriving at an image pixel. Using a conventional Bayer pattern, data…

Image and Video Processing · Electrical Eng. & Systems 2022-02-23 Yung-Hsuan Chao , Haoran Hong , Gene Cheung , Antonio Ortega

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

The deep image prior was recently introduced as a prior for natural images. It represents images as the output of a convolutional network with random inputs. For "inference", gradient descent is performed to adjust network parameters to…

Computer Vision and Pattern Recognition · Computer Science 2019-04-17 Zezhou Cheng , Matheus Gadelha , Subhransu Maji , Daniel Sheldon

Iterative refinement methods based on a denoising-inversion cycle are powerful tools for enhancing the quality and control of diffusion models. However, their effectiveness is critically limited when combined with standard Classifier-Free…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Haosen Li , Wenshuo Chen , Shaofeng Liang , Lei Wang , Haozhe Jia , Yutao Yue

Gaze redirection aims at manipulating the gaze of a given face image with respect to a desired direction (i.e., a reference angle) and it can be applied to many real life scenarios, such as video-conferencing or taking group photos.…

Computer Vision and Pattern Recognition · Computer Science 2020-11-30 Jingjing Chen , Jichao Zhang , Enver Sangineto , Jiayuan Fan , Tao Chen , Nicu Sebe

With the rapid development of deep generative models (such as Generative Adversarial Networks and Diffusion models), AI-synthesized images are now of such high quality that humans can hardly distinguish them from pristine ones. Although…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yan Ju , Shan Jia , Jialing Cai , Haiying Guan , Siwei Lyu

The integration of aerial and ground images has been a promising solution in 3D modeling of complex scenes, which is seriously restricted by finding reliable correspondences. The primary contribution of this study is a feature matching…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Jiangxue Yu , Hui Wang , San Jiang , Xing Zhang , Dejin Zhang , Qingquan Li

Photographic style, as a composition of certain photographic concepts, is the charm behind renowned photographers. But learning and transferring photographic style need a profound understanding of how the photo is edited from the unknown…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Chengxuan Zhu , Shuchen Weng , Jiacong Fang , Peixuan Zhang , Si Li , Chao Xu , Boxin Shi

Image manipulation detection algorithms are often trained to discriminate between images manipulated with particular Generative Models (GMs) and genuine/real images, yet generalize poorly to images manipulated with GMs unseen in the…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Vishal Asnani , Xi Yin , Tal Hassner , Sijia Liu , Xiaoming Liu

Classifier-Free Guidance (CFG) is a widely used technique for conditional generation and improving sample quality in continuous diffusion models, and its extensions to discrete diffusion has recently started to be investigated. In order to…

Machine Learning · Computer Science 2026-03-04 Kevin Rojas , Ye He , Chieh-Hsin Lai , Yuhta Takida , Yuki Mitsufuji , Molei Tao

Producing large images using small diffusion models is gaining increasing popularity, as the cost of training large models could be prohibitive. A common approach involves jointly generating a series of overlapped image patches and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Shoukun Sun , Min Xian , Tiankai Yao , Fei Xu , Luca Capriotti

Solving image inverse problems (e.g., super-resolution and inpainting) requires generating a high fidelity image that matches the given input (the low-resolution image or the masked image). By using the input image as guidance, we can…

Image and Video Processing · Electrical Eng. & Systems 2024-03-19 Haoyue Tang , Tian Xie , Aosong Feng , Hanyu Wang , Chenyang Zhang , Yang Bai

With the growing size of pre-trained models, full fine-tuning and storing all the parameters for various downstream tasks is costly and infeasible. In this paper, we propose a new parameter-efficient fine-tuning method, Gradient-based…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zhi Zhang , Qizhe Zhang , Zijun Gao , Renrui Zhang , Ekaterina Shutova , Shiji Zhou , Shanghang Zhang

Image Restoration has seen remarkable progress in recent years. Many generative models have been adapted to tackle the known restoration cases of images. However, the interest in benefiting from the frequency domain is not well explored…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Bilel Benjdira , Anas M. Ali , Anis Koubaa

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

Recent advances in text-guided image compression have shown great potential to enhance the perceptual quality of reconstructed images. These methods, however, tend to have significantly degraded pixel-wise fidelity, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Hagyeong Lee , Minkyu Kim , Jun-Hyuk Kim , Seungeon Kim , Dokwan Oh , Jaeho Lee

With the advent of sophisticated cameras, the urge to capture high-quality images has grown enormous. However, the noise contamination of the images results in substandard expectations among the people; thus, image denoising is an essential…

Image and Video Processing · Electrical Eng. & Systems 2024-07-19 Kelum Gajamannage , Yonggi Park , S. M. Mallikarjunaiah , Sunil Mathur