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Invertible Neural BRDF for Object Inverse Rendering
[article]
2020
arXiv
pre-print
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We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a single image of an object ...
We also devise a deep illumination prior by leveraging the structural bias of deep neural networks. ...
Lombardi and Nishino [23] use a learned prior for natural materials using the DSBRDF model [31] for multi-material estimation. Kang et al . [17] and Gao et al . ...
arXiv:2008.04030v2
fatcat:e3ubqao2gvgana6si6emn4eb24
Deep Reflectance Maps
[article]
2015
arXiv
pre-print
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In order to analyze performance on this difficult task, we propose a new challenge of Specular MAterials on SHapes with complex IllumiNation (SMASHINg) using both synthetic and real images. ...
We propose a convolutional neural architecture to estimate reflectance maps of specular materials in natural lighting conditions. ...
Our results show truthful reflectance maps in all three investigated scenarios and we demonstrate the applicability on several image-based editing tasks. ...
arXiv:1511.04384v1
fatcat:277f7lbasfafzn6k34yha3hvii
LIME: Live Intrinsic Material Estimation
[article]
2018
arXiv
pre-print
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We present the first end to end approach for real time material estimation for general object shapes with uniform material that only requires a single color image as input. ...
The underlying core representations of our approach are specular shading, diffuse shading and mirror images, which allow to learn the effective and accurate separation of diffuse and specular albedo. ...
Gool, and T. Tuytelaars. Reflectance and natural
illumination from single-material specular objects using deep
learning. ...
arXiv:1801.01075v2
fatcat:bxvrwkxkgnhq5owufhqwzgrfre
LIME: Live Intrinsic Material Estimation
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Our approach enables the real-time estimation of the material of general objects (left) from just a single monocular color image. ...
The underlying core representations of our approach are specular shading, diffuse shading and mirror images, which allow to learn the effective and accurate separation of diffuse and specular albedo. ...
This work was supported by EPSRC grant CAMERA (EP/M023281/1), ERC Starting Grant CapReal (335545), and the Max Planck Center for Visual Computing and Communications (MPC-VCC). ...
doi:10.1109/cvpr.2018.00661
dblp:conf/cvpr/MekaMZCSRT18
fatcat:q5hkphulibfgxotmez5ifls2ym
Deep Reflectance Maps
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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In order to analyze performance on this difficult task, we propose a new challenge of Specular MAterials on SHapes with complex IllumiNation (SMASHINg) using both synthetic and real images. ...
We propose a convolutional neural architecture to estimate reflectance maps of specular materials in natural lighting conditions. ...
Acknowledgements This work is supported by the IWT SBO project PARIS and the FWO project "Representations and algorithms for the captation, visualization and manipulation of moving 3D objects, subjects ...
doi:10.1109/cvpr.2016.488
dblp:conf/cvpr/RematasRFGT16
fatcat:5thra7wcyjh7zlwiuzpjpyvac4
What Is Around The Camera?
[article]
2017
arXiv
pre-print
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The proposed method allows us to jointly model the statistics of environments and material properties. ...
We propose a learning-based approach to predict the environment from multiple reflectance maps that are computed from approximate surface normals. ...
To this end, we took photographs of naturally illuminated singlematerial and multi-material objects with known geometry. ...
arXiv:1611.09325v2
fatcat:z4i4kgth4bce3exr4hd3zjm4qe
A Survey on Intrinsic Images: Delving Deep Into Lambert and Beyond
[article]
2021
arXiv
pre-print
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Deep learning techniques have been broadly applied in recent years to increase the accuracy of those separations. ...
Intrinsic imaging or intrinsic image decomposition has traditionally been described as the problem of decomposing an image into two layers: a reflectance, the albedo invariant color of the material; and ...
While none of the deep learning-based methods use it, the dichromatic reflection model (Section 2.3.2) was also used to account for metallic objects and colored speculars in traditional approaches [130 ...
arXiv:2112.03842v1
fatcat:ciwwxoodq5fl7ma4jqjrgp7k5m
Robust Point Light Source Estimation Using Differentiable Rendering
[article]
2018
arXiv
pre-print
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Illumination estimation is often used in mixed reality to re-render a scene from another point of view, to change the color/texture of an object, or to insert a virtual object consistently lit into a real ...
We compare our differentiable renderer to state-of-the-art methods and demonstrate its robustness to an incorrect reflectance estimation. ...
[27] learn to estimate an intermediate representation that mixes illumination and a single material, called a "reflectance map". ...
arXiv:1812.04857v1
fatcat:aizt5l2tmjce3od3crtgeklr4u
DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination
[article]
2016
arXiv
pre-print
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In this paper we are extracting surface reflectance and natural environmental illumination from a reflectance map, i.e. from a single 2D image of a sphere of one material under one illumination. ...
With the recent advances in estimating reflectance maps from 2D images their further decomposition has become increasingly relevant. ...
Conclusion We have shown how Convolutional Neural Networks (CNNs) can be used to decompose a 2D image of a reflectance map into specular reflectance (material) and complex natural illumination. ...
arXiv:1603.08240v1
fatcat:hubbd5tauba4zgbrbbf3d4osom
Deep Appearance Maps
[article]
2019
arXiv
pre-print
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We propose a deep representation of appearance, i. e., the relation of color, surface orientation, viewer position, material and illumination. ...
Finally, we show the example of an appearance estimation-and-segmentation task, mapping from an image showingmultiple materials to multiple deep appearance maps. ...
Using a single material, the material segmentation is ignored and one random material from the objects is assigned to the entire 3D objects. In the multi-material case, we proceed directly. ...
arXiv:1804.00863v3
fatcat:2hykyu5rzjaazjbxknkuoqzosu
Faces as Lighting Probes via Unsupervised Deep Highlight Extraction
[chapter]
2018
Lecture Notes in Computer Science
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We present a method for estimating detailed scene illumination using human faces in a single image. ...
Based on the observation that faces can exhibit strong highlight reflections from a broad range of lighting directions, we propose a deep neural network for extracting highlights from faces, and then trace ...
Renjiao Yi is supported by scholarship from China Scholarship Council. ...
doi:10.1007/978-3-030-01240-3_20
fatcat:ljaygsbsx5ggxcgvhlbfa5p2ze
Learning Non-Lambertian Object Intrinsics Across ShapeNet Categories
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We consider the non-Lambertian object intrinsic problem of recovering diffuse albedo, shading, and specular highlights from a single image of an object. ...
Rendered with realistic environment maps, millions of synthetic images of objects and their corresponding albedo, shading, and specular ground-truth images are used to train an encoder-decoder CNN. ...
Our model predicts spatially varying albedo maps and supports general lighting conditions. Learning from Rendered Images. Images rendered from 3D models are widely used in deep learning, e.g. ...
doi:10.1109/cvpr.2017.619
dblp:conf/cvpr/ShiDSY17
fatcat:v7jfasg62zdancavcwfd35ypqe
A Method for Estimating Reflectance map and Material using Deep Learning with Synthetic Dataset
[article]
2020
arXiv
pre-print
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In this paper, we propose a deep learning-based reflectance map prediction system for material estimation of target objects in the image, so as to alleviate the ill-posed problem that occurs in this image ...
We get out of the previously proposed Deep Learning-based network architecture for reflectance map, and we newly propose to use conditional Generative Adversarial Network (cGAN) structures for estimating ...
In this work, we extract high quality reflectance maps from images of a target object with complex shapes and specular materials under complex natural illumination. ...
arXiv:2001.05372v1
fatcat:yaqcgbk5ezbpflf56foowkhnxq
Object-based Illumination Estimation with Rendering-aware Neural Networks
[article]
2020
arXiv
pre-print
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This results in a rendering-aware system that estimates the local illumination distribution at an object with high accuracy and in real time. ...
We present a scheme for fast environment light estimation from the RGBD appearance of individual objects and their local image areas. ...
Deep learning has also been applied for illumination estimation from objects. ...
arXiv:2008.02514v1
fatcat:3er3wp6ldrcotiqh26damvv7sq
Material Editing Using a Physically Based Rendering Network
[article]
2017
arXiv
pre-print
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Specifically, given a single image, the network first predicts intrinsic properties, i.e. shape, illumination, and material, which are then provided to a rendering layer. ...
The proposed rendering layer is fully differentiable, supports both diffuse and specular materials, and thus can be applicable in a variety of problem settings. ...
This work is supported by a gift from Adobe, NSF EFRI-1240459, CNS-1205260 and AFOSR FA9550-17-1-0075. ...
arXiv:1708.00106v2
fatcat:g4z7u5uezjdrfom3t4krzeq7ra
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