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Related papers: Learning to See Through Obstructions

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We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera. Our method leverages motion…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Yu-Lun Liu , Wei-Sheng Lai , Ming-Hsuan Yang , Yung-Yu Chuang , Jia-Bin Huang

Reflections are very common phenomena in our daily photography, which distract people's attention from the scene behind the glass. The problem of removing reflection artifacts is important but challenging due to its ill-posed nature. The…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Yingda Yin , Qingnan Fan , Dongdong Chen , Yujie Wang , Angelica Aviles-Rivero , Ruoteng Li , Carola-Bibiane Schnlieb , Baoquan Chen

Image of a scene captured through a piece of transparent and reflective material, such as glass, is often spoiled by a superimposed layer of reflection image. While separating the reflection from a familiar object in an image is mentally…

Computer Vision and Pattern Recognition · Computer Science 2018-02-02 Zhixiang Chi , Xiaolin Wu , Xiao Shu , Jinjin Gu

This paper deals with a challenging, frequently encountered, yet not properly investigated problem in two-frame optical flow estimation. That is, the input frames are compounds of two imaging layers -- one desired background layer of the…

Computer Vision and Pattern Recognition · Computer Science 2016-05-09 Jiaolong Yang , Hongdong Li , Yuchao Dai , Robby T. Tan

Taking photographs ''in-the-wild'' is often hindered by fence obstructions that stand between the camera user and the scene of interest, and which are hard or impossible to avoid. De-fencing is the algorithmic process of automatically…

Computer Vision and Pattern Recognition · Computer Science 2023-01-26 Stavros Tsogkas , Fengjia Zhang , Allan Jepson , Alex Levinshtein

Intrinsic image decomposition, which is an essential task in computer vision, aims to infer the reflectance and shading of the scene. It is challenging since it needs to separate one image into two components. To tackle this, conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-05-28 Yunfei Liu , Yu Li , Shaodi You , Feng Lu

We propose a novel approach that jointly removes reflection or translucent layer from a scene and estimates scene depth. The input data are captured via light field imaging. The problem is couched as minimizing the rank of the transmitted…

Computer Vision and Pattern Recognition · Computer Science 2015-06-16 Qiaosong Wang , Haiting Lin , Yi Ma , Sing Bing Kang , Jingyi Yu

Conventional approaches to image de-fencing use multiple adjacent frames for segmentation of fences in the reference image and are limited to restoring images of static scenes only. In this paper, we propose a de-fencing algorithm for…

Computer Vision and Pattern Recognition · Computer Science 2016-10-24 Sankaraganesh Jonna , Krishna K. Nakka , Rajiv R. Sahay

In this work, we present a novel learning-based approach to synthesize new views of a light field image. In particular, given the four corner views of a light field, the presented method estimates any in-between view. We use three…

Computer Vision and Pattern Recognition · Computer Science 2021-02-19 Julia Navarro , Neus Sabater

Image quality degradation caused by raindrops is one of the most important but challenging problems that reduce the performance of vision systems. Most existing raindrop removal algorithms are based on a supervised learning method using…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Huijiao Wang , Shenghao Zhao , Lei Yu , Xulei Yang

Reflections in videos are obstructions that often occur when videos are taken behind reflective surfaces like glass. These reflections reduce the quality of such videos, lead to information loss and degrade the accuracy of many computer…

Computer Vision and Pattern Recognition · Computer Science 2020-09-08 Amgad Ahmed , Suhong Kim , Mohamed Elgharib , Mohamed Hefeeda

A novel framework of optical image hiding based on deep learning (DL) is proposed in this paper, and hidden information can be reconstructed from an interferogram by using an end to end network with high-quality. By using the prior data…

Image and Video Processing · Electrical Eng. & Systems 2020-03-10 Jiaosheng Li , Yuhui Li , Ju Li , Qinnan Zhang , Guo Yang , Shimei Chen , Chen Wang , Jun Li

Reflections often degrade the quality of the image by obstructing the background scene. This is not desirable for everyday users, and it negatively impacts the performance of multimedia applications that process images with reflections.…

Computer Vision and Pattern Recognition · Computer Science 2020-09-03 Suhong Kim , Hamed RahmaniKhezri , Seyed Mohammad Nourbakhsh , Mohamed Hefeeda

In recent times, the availability of inexpensive image capturing devices such as smartphones/tablets has led to an exponential increase in the number of images/videos captured. However, sometimes the amateur photographer is hindered by…

Computer Vision and Pattern Recognition · Computer Science 2018-05-22 Sankaraganesh Jonna , Krishna Kanth Nakka , Rajiv R. Sahay

This paper studies the problem of language-guided reflection separation, which aims at addressing the ill-posed reflection separation problem by introducing language descriptions to provide layer content. We propose a unified framework to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Haofeng Zhong , Yuchen Hong , Shuchen Weng , Jinxiu Liang , Boxin Shi

Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconvenient for users. We instead propose a learning-based…

Computer Vision and Pattern Recognition · Computer Science 2020-10-05 Simon Niklaus , Xuaner Cecilia Zhang , Jonathan T. Barron , Neal Wadhwa , Rahul Garg , Feng Liu , Tianfan Xue

Photorealistic object appearance modeling from 2D images is a constant topic in vision and graphics. While neural implicit methods (such as Neural Radiance Fields) have shown high-fidelity view synthesis results, they cannot relight the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Hong-Xing Yu , Michelle Guo , Alireza Fathi , Yen-Yu Chang , Eric Ryan Chan , Ruohan Gao , Thomas Funkhouser , Jiajun Wu

When imaging through a semi-reflective medium such as glass, the reflection of another scene can often be found in the captured images. It degrades the quality of the images and affects their subsequent analyses. In this paper, a novel deep…

Image and Video Processing · Electrical Eng. & Systems 2022-08-11 Tingtian Li , Yuk-Hee Chan , Daniel P. K. Lun

Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. Existing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Rong Zou , Manasi Muglikar , Nico Messikommer , Davide Scaramuzza

Obstacle avoidance from monocular images is a challenging problem for robots. Though multi-view structure-from-motion could build 3D maps, it is not robust in textureless environments. Some learning based methods exploit human demonstration…

Robotics · Computer Science 2017-05-01 Shichao Yang , Sandeep Konam , Chen Ma , Stephanie Rosenthal , Manuela Veloso , Sebastian Scherer
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