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Related papers: Shape and Material Capture at Home

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3D geometry is a very informative cue when interacting with and navigating an environment. This writing proposes a new approach to 3D reconstruction and scene understanding, which implicitly learns 3D geometry from depth maps pairing a deep…

Computer Vision and Pattern Recognition · Computer Science 2018-08-22 Dario Rethage , Federico Tombari , Felix Achilles , Nassir Navab

Relighting of human images has various applications in image synthesis. For relighting, we must infer albedo, shape, and illumination from a human portrait. Previous techniques rely on human faces for this inference, based on spherical…

Graphics · Computer Science 2019-08-12 Yoshihiro Kanamori , Yuki Endo

We present a scheme for fast environment light estimation from the RGBD appearance of individual objects and their local image areas. Conventional inverse rendering is too computationally demanding for real-time applications, and the…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Xin Wei , Guojun Chen , Yue Dong , Stephen Lin , Xin Tong

We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photographs with varying cameras, illumination, and backgrounds.…

Computer Vision and Pattern Recognition · Computer Science 2022-09-05 Zhengfei Kuang , Kyle Olszewski , Menglei Chai , Zeng Huang , Panos Achlioptas , Sergey Tulyakov

We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a target and recording the speed-of-light time delay of the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Weihan Luo , Anagh Malik , David B. Lindell

We present a portable device to capture both shape and reflectance of an indoor scene. Consisting of a Kinect, an IR camera and several IR LEDs, our device allows the user to acquire data in a similar way as he/she scans with a single…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Zhe Wu , Sai-Kit Yeung , Ping Tan

Estimating surface reflectance (BRDF) is one key component for complete 3D scene capture, with wide applications in virtual reality, augmented reality, and human computer interaction. Prior work is either limited to controlled environments…

Computer Vision and Pattern Recognition · Computer Science 2018-04-03 Kihwan Kim , Jinwei Gu , Stephen Tyree , Pavlo Molchanov , Matthias Nießner , Jan Kautz

Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Hadi Alzayer , Philipp Henzler , Jonathan T. Barron , Jia-Bin Huang , Pratul P. Srinivasan , Dor Verbin

We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360$^{\circ}$ stereo images. Our model takes advantage of the 360$^{\circ}$ input to observe the entire scene with…

Computer Vision and Pattern Recognition · Computer Science 2021-04-21 Junxuan Li , Hongdong Li , Yasuyuki Matsushita

Estimating the layout of a room from a single-shot panoramic image is important in virtual/augmented reality and furniture layout simulation. This involves identifying three-dimensional (3D) geometry, such as the location of corners and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Mizuki Tabata , Kana Kurata , Junichiro Tamamatsu

This paper introduces single-image geometric and appearance reconstruction from water reflection photography, i.e., images capturing direct and water-reflected real-world scenes. Water reflection offers an additional viewpoint to the direct…

Computer Vision and Pattern Recognition · Computer Science 2020-01-08 Ryo Kawahara , Meng-Yu Jennifer Kuo , Shohei Nobuhara , Ko Nishino

We present a technique for estimating the shape and reflectance of an object in terms of its surface normals and spatially-varying BRDF. We assume that multiple images of the object are obtained under fixed view-point and varying…

Computer Vision and Pattern Recognition · Computer Science 2015-03-17 Zhuo Hui , Aswin C. Sankaranarayanan

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

Computer vision has long relied on two kinds of correspondences: pixel correspondences in images and 3D correspondences on object surfaces. Is there another kind, and if there is, what can they do for us? In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Kohei Yamashita , Vincent Lepetit , Ko Nishino

Light spectra are a very important source of information for diverse classification problems, e.g., for discrimination of materials. To lower the cost for acquiring this information, multispectral cameras are used. Several techniques exist…

Image and Video Processing · Electrical Eng. & Systems 2022-09-19 Frank Sippel , Jürgen Seiler , Nils Genser , André Kaup

Lighting plays a central role in conveying the essence and depth of the subject in a portrait photograph. Professional photographers will carefully control the lighting in their studio to manipulate the appearance of their subject, while…

Transparent objects are widely used in our daily lives, making it important to teach robots to interact with them. However, it's not easy because the reflective and refractive effects can make depth cameras fail to give accurate geometry…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Tutian Tang , Jiyu Liu , Jieyi Zhang , Haoyuan Fu , Wenqiang Xu , Cewu Lu

Recently, significant progress has been made in the study of methods for 3D reconstruction from multiple images using implicit neural representations, exemplified by the neural radiance field (NeRF) method. Such methods, which are based on…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Wooseok Kim , Taiki Fukiage , Takeshi Oishi

Recovering the radiometric properties of a scene (i.e., the reflectance, illumination, and geometry) is a long-sought ability of computer vision that can provide invaluable information for a wide range of applications. Deciphering the…

Computer Vision and Pattern Recognition · Computer Science 2016-04-06 Stephen Lombardi , Ko Nishino

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2014-09-16 Ju Shen , Jianjun Yang , Sami Taha-abusneineh , Bryson Payne , Markus Hitz