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We present a novel formulation to removing reflection from polarized images in the wild. We first identify the misalignment issues of existing reflection removal datasets where the collected reflection-free images are not perfectly aligned…

Computer Vision and Pattern Recognition · Computer Science 2020-03-31 Chenyang Lei , Xuhua Huang , Mengdi Zhang , Qiong Yan , Wenxiu Sun , Qifeng 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

3D Gaussian Splatting (3D-GS) has made a notable advancement in the field of neural rendering, 3D scene reconstruction, and novel view synthesis. Nevertheless, 3D-GS encounters the main challenge when it comes to accurately representing…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Rui Zhang , Tianyue Luo , Weidong Yang , Ben Fei , Jingyi Xu , Qingyuan Zhou , Keyi Liu , Ying He

Flash illumination is widely used in imaging under low-light environments. However, illumination intensity falls off with propagation distance quadratically, which poses significant challenges for flash imaging at a long distance. We…

Image and Video Processing · Electrical Eng. & Systems 2022-07-27 Zhanghao Sun , Jian Wang , Yicheng Wu , Shree Nayar

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

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical images (whether focused by lenses or not) are diffraction…

Optics · Physics 2021-04-08 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta

Glass surfaces are ubiquitous in daily life, typically appearing colorless, transparent, and lacking distinctive features. These characteristics make glass surface detection a challenging computer vision task. Existing glass surface…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Tao Yan , Hao Huang , Yiwei Lu , Zeyu Wang , Ke Xu , Yinghui Wang , Xiaojun Chang , Rynson W. H. Lau

Gaussian Splatting is a powerful tool for reconstructing diffuse scenes, but it struggles to simultaneously model specular reflections and the appearance of objects behind semi-transparent surfaces. These specular reflections and…

Graphics · Computer Science 2026-04-02 Kunnong Zeng , Chensheng Peng , Yichen Xie , Masayoshi Tomizuka , Cem Yuksel

In this paper, we address the problem of reflection removal and deblurring from a single image captured by a plenoptic camera. We develop a two-stage approach to recover the scene depth and high resolution textures of the reflected and…

Computer Vision and Pattern Recognition · Computer Science 2017-08-24 Paramanand Chandramouli , Mehdi Noroozi , Paolo Favaro

Diffusion models have recently motivated great success in many generation tasks like object removal. Nevertheless, existing image decomposition methods struggle to disentangle semi-transparent or transparent layer occlusions due to mask…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zitong Wang , Hang Zhao , Qianyu Zhou , Xuequan Lu , Xiangtai Li , Yiren Song

Fringe projection profilometry-based 3-D reconstruction of objects with high reflectivity and low surface roughness remains a significant challenge. When measuring such glossy surfaces, specular reflection and indirect illumination often…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Sanghoon Jeon , Gihyun Jung , Suhyeon Ka , Jae-Sang Hyun

The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance to their surroundings, transparent objects are not handled…

Computer Vision and Pattern Recognition · Computer Science 2015-11-24 Yichao Xu , Hajime Nagahara , Atsushi Shimada , Rin-ichiro Taniguchi

Accurately rendering scenes with reflective surfaces remains a significant challenge in novel view synthesis, as existing methods like Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) often misinterpret reflections as physical…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Jiayi Song , Zihan Ye , Qingyuan Zhou , Weidong Yang , Ben Fei , Jingyi Xu , Ying He , Wanli Ouyang

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

Computer Vision and Pattern Recognition · Computer Science 2020-04-03 Yu-Lun Liu , Wei-Sheng Lai , Ming-Hsuan Yang , Yung-Yu Chuang , Jia-Bin Huang

Summary. A modified version of the two-slit experiment is proposed in which the moveable detector/counter used to obtain the fringe distribution by counting single photons at different positions on the screen plane is replaced with a mirror…

Quantum Physics · Physics 2007-05-23 G. Sampath

We introduce a diffusion-transformer (DiT) framework for single-image reflection removal that leverages the generalization strengths of foundation diffusion models in the restoration setting. Rather than relying on task-specific…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Daniyar Zakarin , Thiemo Wandel , Anton Obukhov , Dengxin Dai

The traditional wisdom for achieving transparency is to minimize disordered scattering within and on the surface of materials, so as to avoid translucency. However, the lack of disordered scattering also deprives the possibility of…

Shadows are common aspect of images and when left undetected can hinder scene understanding and visual processing. We propose a simple yet effective approach based on reflectance to detect shadows from single image. An image is first…

Computer Vision and Pattern Recognition · Computer Science 2018-07-13 Sri Kalyan Yarlagadda , Fengqing Zhu

Transmissive scenes are ubiquitous in daily life, yet reconstructing and rendering them remains highly challenging due to the inherent entanglement between near-field reflections from the surrounding environment on the transmissive surface,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhenyu Liang , Xiao Zhang , Tianchao Li , Jack C. P. Cheng , Chi-Keung Tang

Photographs taken through a glass surface often contain an approximately linear superposition of reflected and transmitted layers. Decomposing an image into these layers is generally an ill-posed task and the use of an additional image…

Computer Vision and Pattern Recognition · Computer Science 2017-05-11 Ofer Springer , Yair Weiss