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Our goal in this work is to generate realistic videos given just one initial frame as input. Existing unsupervised approaches to this task do not consider the fact that a video typically shows a 3D environment, and that this should remain…

Computer Vision and Pattern Recognition · Computer Science 2021-06-18 Paul Henderson , Christoph H. Lampert , Bernd Bickel

Single-image super-resolution (SR) and multi-frame SR are two ways to super resolve low-resolution images. Single-Image SR generally handles each image independently, but ignores the temporal information implied in continuing frames.…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Wenjia Niu , Kaihao Zhang , Wenhan Luo , Yiran Zhong

Video deblurring is a challenging task due to the spatially variant blur caused by camera shake, object motions, and depth variations, etc. Existing methods usually estimate optical flow in the blurry video to align consecutive frames or…

Computer Vision and Pattern Recognition · Computer Science 2019-08-02 Shangchen Zhou , Jiawei Zhang , Jinshan Pan , Haozhe Xie , Wangmeng Zuo , Jimmy Ren

Image research has shown substantial attention in deblurring networks in recent years. Yet, their practical usage in real-world deblurring, especially motion blur, remains limited due to the lack of pixel-aligned training triplets…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Simin Luan , Cong Yang , Zeyd Boukhers , Xue Qin , Dongfeng Cheng , Wei Sui , Zhijun Li

Several state-of-the-art video deblurring methods are based on a strong assumption that the captured scenes are static. These methods fail to deblur blurry videos in dynamic scenes. We propose a video deblurring method to deal with general…

Computer Vision and Pattern Recognition · Computer Science 2015-07-10 Tae Hyun Kim , Kyoung Mu Lee

We propose a novel framework to reconstruct super-resolution human shape from a single low-resolution input image. The approach overcomes limitations of existing approaches that reconstruct 3D human shape from a single image, which require…

Computer Vision and Pattern Recognition · Computer Science 2022-08-24 Marco Pesavento , Marco Volino , Adrian Hilton

Blind single image deblurring has been a challenge over many decades due to the ill-posed nature of the problem. In this paper, we propose a single-frame blind deblurring solution with the aid of Laplacian filters. Utilized Residual Dense…

Image and Video Processing · Electrical Eng. & Systems 2020-09-18 Baran Ataman , Esin Guldogan

State-of-the-art video deblurring methods cannot handle blurry videos recorded in dynamic scenes, since they are built under a strong assumption that the captured scenes are static. Contrary to the existing methods, we propose a video…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Tae Hyun Kim , Seungjun Nah , Kyoung Mu Lee

In this paper, we present a new inpainting framework for recovering missing regions of video frames. Compared with image inpainting, performing this task on video presents new challenges such as how to preserving temporal consistency and…

Computer Vision and Pattern Recognition · Computer Science 2019-05-09 Yifan Ding , Chuan Wang , Haibin Huang , Jiaming Liu , Jue Wang , Liqiang Wang

The objective of this work is to deblur face videos. We propose a method that tackles this problem from two directions: (1) enhancing the blurry frames, and (2) treating the blurry frames as missing values and estimate them by…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 Phong Tran , Anh Tran , Thao Nguyen , Minh Hoai

Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras, however, fast motion can be captured as events at high time…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Zhe Jiang , Yu Zhang , Dongqing Zou , Jimmy Ren , Jiancheng Lv , Yebin Liu

Video imaging is often affected by complex degradations such as blur, noise, and compression artifacts. Traditional restoration methods follow a "single-task single-model" paradigm, resulting in poor generalization and high computational…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shuning Sun , Yu Zhang , Chen Wu , Dianjie Lu , Dianjie Lu , Guijuan Zhan , Yang Weng , Zhuoran Zheng

One of the solutions of depth imaging of moving scene is to project a static pattern on the object and use just a single image for reconstruction. However, if the motion of the object is too fast with respect to the exposure time of the…

Computer Vision and Pattern Recognition · Computer Science 2017-10-03 Yuki Shiba , Satoshi Ono , Ryo Furukawa , Shinsaku Hiura , Hiroshi Kawasaki

Visual images corrupted by various types and levels of degradations are commonly encountered in practical image compression. However, most existing image compression methods are tailored for clean images, therefore struggling to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Huimin Zeng , Jiacheng Li , Ziqiang Zheng , Zhiwei Xiong

We present an algorithm for reconstructing dense, geometrically consistent depth for all pixels in a monocular video. We leverage a conventional structure-from-motion reconstruction to establish geometric constraints on pixels in the video.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Xuan Luo , Jia-Bin Huang , Richard Szeliski , Kevin Matzen , Johannes Kopf

Super-Resolution from a single motion Blurred image (SRB) is a severely ill-posed problem due to the joint degradation of motion blurs and low spatial resolution. In this paper, we employ events to alleviate the burden of SRB and propose an…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Lei Yu , Bishan Wang , Xiang Zhang , Haijian Zhang , Wen Yang , Jianzhuang Liu , Gui-Song Xia

Blind motion deblurring involves reconstructing a sharp image from an observation that is blurry. It is a problem that is ill-posed and lies in the categories of image restoration problems. The training data-based methods for image…

Computer Vision and Pattern Recognition · Computer Science 2020-11-10 Harshil Jain , Rohit Patil , Indra Deep Mastan , Shanmuganathan Raman

This paper presents a unified framework that allows high-quality dynamic Gaussian Splatting from both defocused and motion-blurred monocular videos. Due to the significant difference between the formation processes of defocus blur and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Xuankai Zhang , Junjin Xiao , Qing Zhang

We present an inverse image-formation module that can enhance the robustness of existing visual SLAM pipelines for casually captured scenarios. Casual video captures often suffer from motion blur and varying appearances, which degrade the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Gwangtak Bae , Changwoon Choi , Hyeongjun Heo , Sang Min Kim , Young Min Kim

As a widely studied task, video restoration aims to enhance the quality of the videos with multiple potential degradations, such as noises, blurs and compression artifacts. Among video restorations, compressed video quality enhancement and…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Meisong Zheng , Qunliang Xing , Minglang Qiao , Mai Xu , Lai Jiang , Huaida Liu , Ying Chen
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