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Video matting has broad applications, from adding interesting effects to casually captured movies to assisting video production professionals. Matting with associated effects such as shadows and reflections has also attracted increasing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Geng Lin , Chen Gao , Jia-Bin Huang , Changil Kim , Yipeng Wang , Matthias Zwicker , Ayush Saraf

We present SlowFast networks for video recognition. Our model involves (i) a Slow pathway, operating at low frame rate, to capture spatial semantics, and (ii) a Fast pathway, operating at high frame rate, to capture motion at fine temporal…

Computer Vision and Pattern Recognition · Computer Science 2019-10-30 Christoph Feichtenhofer , Haoqi Fan , Jitendra Malik , Kaiming He

Leveraging the generative ability of image diffusion models offers great potential for zero-shot video-to-video translation. The key lies in how to maintain temporal consistency across generated video frames by image diffusion models.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yuxiang Bao , Di Qiu , Guoliang Kang , Baochang Zhang , Bo Jin , Kaiye Wang , Pengfei Yan

Automatic video colorization is inherently an ill-posed problem because each monochrome frame has multiple optional color candidates. Previous exemplar-based video colorization methods restrict the user's imagination due to the elaborate…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Zheng Chang , Shuchen Weng , Huan Ouyang , Yu Li , Si Li , Boxin Shi

Diffusion models have demonstrated remarkable success in image generation and editing, with recent advancements enabling albedo-preserving image relighting. However, applying these models to video relighting remains challenging due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ye Fang , Zeyi Sun , Shangzhan Zhang , Tong Wu , Yinghao Xu , Pan Zhang , Jiaqi Wang , Gordon Wetzstein , Dahua Lin

Abrupt motion of camera or objects in a scene result in a blurry video, and therefore recovering high quality video requires two types of enhancements: visual enhancement and temporal upsampling. A broad range of research attempted to…

Computer Vision and Pattern Recognition · Computer Science 2021-03-11 Dawit Mureja Argaw , Junsik Kim , Francois Rameau , In So Kweon

Homographies -- a mathematical formalism for relating image points across different camera viewpoints -- are at the foundations of geometric methods in computer vision and are used in geometric camera calibration, image registration, and…

Computer Vision and Pattern Recognition · Computer Science 2016-08-02 Graham D. Finlayson , Han Gong , Robert B. Fisher

Photographs captured by smartphones and mid-range cameras have limited spatial resolution and dynamic range, with noisy response in underexposed regions and color artefacts in saturated areas. This paper introduces the first approach (to…

Computer Vision and Pattern Recognition · Computer Science 2022-08-01 Bruno Lecouat , Thomas Eboli , Jean Ponce , Julien Mairal

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack of temporally consistent handling of plausible clothing…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Moritz Kappel , Vladislav Golyanik , Mohamed Elgharib , Jann-Ole Henningson , Hans-Peter Seidel , Susana Castillo , Christian Theobalt , Marcus Magnor

Although diffusion-based zero-shot image restoration and enhancement methods have achieved great success, applying them to video restoration or enhancement will lead to severe temporal flickering. In this paper, we propose the first…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Cong Cao , Huanjing Yue , Shangbin Xie , Xin Liu , Jingyu Yang

Video semantic segmentation aims to generate accurate semantic maps for each video frame. To this end, many works dedicate to integrate diverse information from consecutive frames to enhance the features for prediction, where a feature…

Computer Vision and Pattern Recognition · Computer Science 2023-01-11 Jiafan Zhuang , Zilei Wang , Junjie Li

Accurate calibration of camera intrinsic parameters is crucial to various computer vision-based applications in the fields of intelligent systems, autonomous vehicles, etc. However, existing calibration schemes are incompetent for finding…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Hsin-Yi Chen , Chuan-Kai Fu , Jen-Hui Chuang

Video Diffusion Models (VDMs) can generate high-quality videos, but often struggle with producing temporally coherent motion. Optical flow supervision is a promising approach to address this, with prior works commonly employing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Kuanting Wu , Kei Ota , Asako Kanezaki

Capturing digital screens with smartphones frequently induces severe banding due to hardware synchronization mismatches. Existing video restoration methods struggle with these structured, periodic luminance fluctuations, often resulting in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Zhiyi Zhou , Libo Zhu , Zihan Zhou , Yulun Zhang , Xiaokang Yang

In this paper, we tackle the problem of video alignment, the process of matching the frames of a pair of videos containing similar actions. The main challenge in video alignment is that accurate correspondence should be established despite…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Niloufar Fakhfour , Mohammad ShahverdiKondori , Sajjad Hashembeiki , Mohammadjavad Norouzi , Hoda Mohammadzade

Modern camera pipelines apply extensive on-device processing, such as exposure adjustment, white balance, and color correction, which, while beneficial individually, often introduce photometric inconsistencies across views. These appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Jisu Shin , Richard Shaw , Seunghyun Shin , Zhensong Zhang , Hae-Gon Jeon , Eduardo Perez-Pellitero

We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes. Most conventional structure from motion and monocular SLAM techniques assume input…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Zhengqi Li , Richard Tucker , Forrester Cole , Qianqian Wang , Linyi Jin , Vickie Ye , Angjoo Kanazawa , Aleksander Holynski , Noah Snavely

In many video restoration/translation tasks, image processing operations are na\"ively extended to the video domain by processing each frame independently, disregarding the temporal connection of the video frames. This disregard for the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Muhammad Kashif Ali , Dongjin Kim , Tae Hyun Kim

We present a method to estimate depth of a dynamic scene, containing arbitrary moving objects, from an ordinary video captured with a moving camera. We seek a geometrically and temporally consistent solution to this underconstrained…

Computer Vision and Pattern Recognition · Computer Science 2021-08-04 Zhoutong Zhang , Forrester Cole , Richard Tucker , William T. Freeman , Tali Dekel

A number of computer vision tasks exploit a succinct representation of the visual content in the form of sets of local features. Given an input image, feature extraction algorithms identify a set of keypoints and assign to each of them a…

Computer Vision and Pattern Recognition · Computer Science 2016-11-18 Luca Baroffio , Matteo Cesana , Alessandro Redondi , Marco Tagliasacchi
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