Learning to minify photometric stereo
Nettet1. mar. 2024 · In this paper, we present a complete photometric stereo data acquisition and processing framework, as shown in Fig. 1, constructing inter- and intraframe feature representations based on an arbitrary number of unordered images captured under different lighting configurations for high-quality surface normal estimation of non … Nettet1. jun. 2024 · This paper reviews existing data-driven methods, with a focus on their technical insights into the photometric stereo problem. We divide these methods into …
Learning to minify photometric stereo
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Nettet13. nov. 2024 · Photometric stereo aims at recovering the surface normals of a scene from single-viewpoint imagery captured under varying light directions [47, 50].In contrast to multi-view stereo [], photometric stereo works well for textureless surfaces and can recover highly detailed surface geometry.Following the conventional assumption, this … Nettet17. mai 2024 · Photometric stereo is a technique for estimating normals of an object surface from its images taken under different light source directions. In general, …
NettetPhotometric stereo aims to recover the surface normals of a 3D object from various shading cues, establishing the relationship between two-dimensional images and the object geometry. Traditional methods usually adopt simplified reflectance models to approximate the non-Lambertian surface properties, while recently, photometric … NettetPDF - Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the …
Nettet1. apr. 2024 · Photometric stereo is a technique for estimating the surface normal of an object by a set of images captured under different lighting conditions. Generally speaking, the literature can be divided into four groups, i.e., example based methods, least-squares methods, robust methods and deep learning methods [1], [2], [3]. NettetImplement Learning-to-Minify-Photometric-Stereo with how-to, Q&A, fixes, code snippets. kandi ratings - Low support, No Bugs, No Vulnerabilities. No License, Build not available.
Nettet23. okt. 2024 · Single-View Photometric Stereo (PS). Traditional PS methods rely on outlier rejection [37, 58, 59], reflectance model fitting [10, 18, 51], or exemplars [15, 16] to deal with non-Lambertian surfaces.Deep learning based PS methods solve this problem by learning the surface reflectance prior from a dataset [7, 8, 17, 31, 44, 49].These …
Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the image formation process, recent photometric stereo methods demand a large number of images as input. We propose a method that can dramatically decrease the demands on the number of images by learning the most informative ones under ... robert longo gretchenNettetThis is the code of paper "Learning to minify photometric stereo, CVPR2024". The code is based on python and keras. - Learning-to-Minify-Photometric-Stereo/README.md at master · junxuan-l... robert longman slaughter and mayNettet25. nov. 2024 · The photometric stereo (PS) problem consists in reconstructing the 3D-surface of an object, thanks to a set of photographs taken under different lighting directions. In this paper, we propose a ... robert longstreth deathNettetand deep-learning based photometric stereo methods for non-Lambertian objects. For a detailed introduction of recent stud-ies of photometricstereo, readers can refer to [14]. … robert longworth obituaryrobert longo workNettetand deep-learning based photometric stereo methods for non-Lambertian objects. For a detailed introduction of recent stud-ies of photometricstereo, readers can refer to [14]. 2.1. Conventionalmethods The original photometric stereo method [8] works based on the ideal Lambertian reflectance model and analyses per-pixel lighting observation ... robert longo artistNettetCVF Open Access robert longyear artist