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Existing portrait matting methods either require auxiliary inputs that are costly to obtain or involve multiple stages that are computationally expensive, making them less suitable for real-time applications. In this work, we present a…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Zhanghan Ke , Jiayu Sun , Kaican Li , Qiong Yan , Rynson W. H. Lau

To achieve visual consistency in composite images, recent image harmonization methods typically summarize the appearance pattern of global background and apply it to the global foreground without location discrepancy. However, for a real…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Ziyue Zhu , Zhao Zhang , Zheng Lin , Ruiqi Wu , Zhi Chai , Chun-Le Guo

This paper proposes a novel pseudo multi-exposure image fusion method based on a single image. Multi-exposure image fusion is used to produce images without saturation regions, by using photos with different exposures. However, it is…

Computer Vision and Pattern Recognition · Computer Science 2018-11-14 Yuma Kinoshita , Sayaka Shiota , Hitoshi Kiya

Restoring and inpainting the visual memories that are present, but often impaired, in old photos remains an intriguing but unsolved research topic. Decades-old photos often suffer from severe and commingled degradation such as cracks,…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Runsheng Xu , Zhengzhong Tu , Yuanqi Du , Xiaoyu Dong , Jinlong Li , Zibo Meng , Jiaqi Ma , Alan Bovik , Hongkai Yu

We propose to restore old photos that suffer from severe degradation through a deep learning approach. Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-16 Ziyu Wan , Bo Zhang , Dongdong Chen , Pan Zhang , Dong Chen , Jing Liao , Fang Wen

We introduce PhotoBot, a framework for fully automated photo acquisition based on an interplay between high-level human language guidance and a robot photographer. We propose to communicate photography suggestions to the user via reference…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Oliver Limoyo , Jimmy Li , Dmitriy Rivkin , Jonathan Kelly , Gregory Dudek

Visual Localization is one of the key enabling technologies for autonomous driving and augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) reference poses are the foundation for benchmarking and improving…

Computer Vision and Pattern Recognition · Computer Science 2021-01-01 Zichao Zhang , Torsten Sattler , Davide Scaramuzza

While physically-based rendering (PBR) simulates light transport that guarantees physical realism, achieving true photorealistic rendering (PRR) demands prohibitive time and labor, and still struggles to capture the intractable richness of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Jiayuan Lu , Rengan Xie , Xuancheng Jin , Zhizhen Wu , Qi Ye , Tian Xie , Hujun Bao , Rui Wang. Yuchi Huo

Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications. Although photo extrapolation has been well studied, it is much more challenging to…

Computer Vision and Pattern Recognition · Computer Science 2022-07-15 Boming Zhao , Bangbang Yang , Zhenyang Li , Zuoyue Li , Guofeng Zhang , Jiashu Zhao , Dawei Yin , Zhaopeng Cui , Hujun Bao

Currently, there are two popular approaches for addressing real-world image super-resolution problems: degradation-estimation-based and blind-based methods. However, degradation-estimation-based methods may be inaccurate in estimating the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Axi Niu , Kang Zhang , Trung X. Pham , Pei Wang , Jinqiu Sun , In So Kweon , Yanning Zhang

Photorealistic style transfer aims to transfer the style of one image to another, but preserves the original structure and detail outline of the content image, which makes the content image still look like a real shot after the style…

Computer Vision and Pattern Recognition · Computer Science 2019-04-29 Ming Li , Chunyang Ye , Wei Li

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

The task of synthesizing novel views from a single image is highly ill-posed due to multiple explanations for unobserved areas. Most current methods tend to generate unseen regions from ambiguity priors and interpolation near input views,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Haowang Cui , Rui Chen , Jiaze Wang , Tao Guo , Zheng Qin

Universal style transfer is an image editing task that renders an input content image using the visual style of arbitrary reference images, including both artistic and photorealistic stylization. Given a pair of images as the source of…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Jie An , Haoyi Xiong , Jiebo Luo , Jun Huan , Jinwen Ma

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images from one single area in the low resolution (LR) input, which…

Computer Vision and Pattern Recognition · Computer Science 2017-05-16 Xiaoyi Jia , Xiangmin Xu , Bolun Cai , Kailing Guo

We introduce NaturalInversion, a novel model inversion-based method to synthesize images that agrees well with the original data distribution without using real data. In NaturalInversion, we propose: (1) a Feature Transfer Pyramid which…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Yujin Kim , Dogyun Park , Dohee Kim , Suhyun Kim

Photorealistic style transfer is a technique which transfers colour from one reference domain to another domain by using deep learning and optimization techniques. Here, we present a technique which we use to transfer style and colour from…

Computer Vision and Pattern Recognition · Computer Science 2018-07-03 Michael Honke , Rahul Iyer , Dishant Mittal

The ability to produce convincing textural details is essential for the fidelity of synthesized person images. However, existing methods typically follow a ``warping-based'' strategy that propagates appearance features through the same…

Computer Vision and Pattern Recognition · Computer Science 2020-10-12 Lingbo Yang , Pan Wang , Xinfeng Zhang , Shanshe Wang , Zhanning Gao , Peiran Ren , Xuansong Xie , Siwei Ma , Wen Gao

Image superresolution involves the processing of an image sequence to generate a still image with higher resolution. Classical approaches, such as bayesian MAP methods, require iterative minimization procedures, with high computational…

Computer Vision and Pattern Recognition · Computer Science 2016-08-31 Carlos Miravet , Francisco B. Rodriguez

This paper introduces a deep-learning approach to photographic style transfer that handles a large variety of image content while faithfully transferring the reference style. Our approach builds upon the recent work on painterly transfer…

Computer Vision and Pattern Recognition · Computer Science 2017-04-12 Fujun Luan , Sylvain Paris , Eli Shechtman , Kavita Bala