Search Results for author:
Found 43 papers, 11 papers with code
What is Learned in Deep Uncalibrated Photometric Stereo?
Based on this insight, we propose a guided calibration network, named GCNet, that explicitly leverages object shape and shading information for improved lighting estimation.
An Analysis of Sketched IRLS for Accelerated Sparse Residual Regression
This paper studies the problem of sparse residual regression, i. e., learning a linear model using a norm that favors solutions in which the residuals are sparsely distributed.
Deep near-light photometric stereo for spatially varying reflectances
This paper presents a near-light photometric stereo method for spatially varying reflectances.
Shadow Art Kanji: Inverse Rendering Application
Finding a balance between artistic beauty and machine-generated imagery is always a difficult task.
DiLiGenRT: A Photometric Stereo Dataset with Quantified Roughness and Translucency
Photometric stereo faces challenges from non-Lambertian reflectance in real-world scenarios.
MVCPS-NeuS: Multi-view Constrained Photometric Stereo for Neural Surface Reconstruction
Multi-view photometric stereo (MVPS) recovers a high-fidelity 3D shape of a scene by benefiting from both multi-view stereo and photometric stereo.
Multi-View Azimuth Stereo via Tangent Space Consistency
We present a method for 3D reconstruction only using calibrated multi-view surface azimuth maps.
Edge-preserving Near-light Photometric Stereo with Neural Surfaces
This paper presents a near-light photometric stereo method that faithfully preserves sharp depth edges in the 3D reconstruction.
Lighting, Reflectance and Geometry Estimation From 360deg Panoramic Stereo
We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360deg stereo images.
Normal Integration via Inverse Plane Fitting With Minimum Point-to-Plane Distance
Experimental results on analytically computed, synthetic, and real-world surfaces show that our method yields accurate and stable reconstruction for both orthographic and perspective normal maps.
Multispectral Photometric Stereo for Spatially-Varying Spectral Reflectances: A Well Posed Problem?
To make the problem well-posed, existing MPS methods rely on restrictive assumptions, such as shape prior, surfaces having a monochromatic with uniform albedo.
Shell Theory: A Statistical Model of Reality
The foundational assumption of machine learning is that the data under consideration is separable into classes; while intuitively reasonable, separability constraints have proven remarkably difficult to formulate mathematically.
Ranked #1 on
Unsupervised Anomaly Detection with Specified Settings -- 10% anomaly
on STL-10
(using extra training data)
Lighting, Reflectance and Geometry Estimation from 360$^{\circ}$ Panoramic Stereo
We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360$^{\circ}$ stereo images.
Generalized Shuffled Linear Regression
Therefore, in this work, we generalize the formulation of shuffled linear regression to a broader range of conditions where only part of the data should correspond.
A Closer Look at Rotation-Invariant Deep Point Cloud Analysis
Recent progress in rotation-invariant point cloud analysis is mainly driven by converting point clouds into their respective canonical poses, and principal component analysis (PCA) is a practical tool to achieve this.
Descriptor-Free Multi-View Region Matching for Instance-Wise 3D Reconstruction
This paper proposes a multi-view extension of instance segmentation without relying on texture or shape descriptor matching.
Deep Photometric Stereo for Non-Lambertian Surfaces
To deal with the uncalibrated scenario where light directions are unknown, we introduce a new convolutional network, named LCNet, to estimate light directions from input images.
Self-calibrating Deep Photometric Stereo Networks
This paper proposes an uncalibrated photometric stereo method for non-Lambertian scenes based on deep learning.
Shape-conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data
Conditional image generation is effective for diverse tasks including training data synthesis for learning-based computer vision.
Light Structure from Pin Motion: Simple and Accurate Point Light Calibration for Physics-based Modeling
We present a practical method for geometric point light source calibration.
Uncalibrated Photometric Stereo Under Natural Illumination
This paper presents a photometric stereo method that works with unknown natural illuminations without any calibration object.
Probabilistic Plant Modeling via Multi-View Image-to-Image Translation
This paper describes a method for inferring three-dimensional (3D) plant branch structures that are hidden under leaves from multi-view observations.
Dimensionality's Blessing: Clustering Images by Underlying Distribution
Many high dimensional vector distances tend to a constant.
Radiometric Calibration for Internet Photo Collections
Radiometrically calibrating the images from Internet photo collections brings photometric analysis from lab data to big image data in the wild, but conventional calibration methods cannot be directly applied to such image data.
GMS: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence
Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching.
Material Classification Using Frequency- and Depth-Dependent Time-Of-Flight Distortion
This paper presents a material classification method using an off-the-shelf Time-of-Flight (ToF) camera.
A Pseudo-Bayesian Algorithm for Robust PCA
Commonly used in many applications, robust PCA represents an algorithmic attempt to reduce the sensitivity of classical PCA to outliers.
Multiview Rectification of Folded Documents
Digitally unwrapping images of paper sheets is crucial for accurate document scanning and text recognition.
A Holistic Approach to Cross-Channel Image Noise Modeling and Its Application to Image Denoising
Modelling and analyzing noise in images is a fundamental task in many computer vision systems.
Recovering Transparent Shape From Time-Of-Flight Distortion
This paper presents a method for recovering shape and normal of a transparent object from a single viewpoint using a Time-of-Flight (ToF) camera.
Continuous 3D Label Stereo Matching using Local Expansion Moves
The local expansion moves extend traditional expansion moves by two ways: localization and spatial propagation.
RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints
We propose a Convolutional Neural Network (CNN)-based model "RotationNet," which takes multi-view images of an object as input and jointly estimates its pose and object category.
Pseudo-Bayesian Robust PCA: Algorithms and Analyses
Commonly used in computer vision and other applications, robust PCA represents an algorithmic attempt to reduce the sensitivity of classical PCA to outliers.
Photometric Stereo With Small Angular Variations
This paper studies the effect of small angular variations in illumination directions to photometric stereo.
Fast Randomized Singular Value Thresholding for Low-rank Optimization
The problems related to NNM, or WNNM, can be solved iteratively by applying a closed-form proximal operator, called Singular Value Thresholding (SVT), or Weighted SVT, but they suffer from high computational cost of Singular Value Decomposition (SVD) at each iteration.
Recovering Inner Slices of Translucent Objects by Multi-Frequency Illumination
This paper describes a method for recovering appearance of inner slices of translucent objects.
Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization
The problems related to NNM (or WNNM) can be solved iteratively by applying a closed-form proximal operator, called Singular Value Thresholding (SVT) (or Weighted SVT), but they suffer from high computational cost to compute a Singular Value Decomposition (SVD) at each iteration.
Superdifferential Cuts for Binary Energies
We then present our method as generalization of SSP, which is further shown to generalize several state-of-the-art techniques for higher-order and pairwise non-submodular functions [Ayed13, Gorelick14, Tang14].
Graph Cut based Continuous Stereo Matching using Locally Shared Labels
We present an accurate and efficient stereo matching method using locally shared labels, a new labeling scheme that enables spatial propagation in MRF inference using graph cuts.
Learning-by-Synthesis for Appearance-based 3D Gaze Estimation
Unlike existing appearance-based methods that assume person-specific training data, we use a large amount of cross-subject training data to train a 3D gaze estimator.
Calibrating a Non-isotropic Near Point Light Source using a Plane
We show that a non-isotropic near point light source rigidly attached to a camera can be calibrated using multiple images of a weakly textured planar scene.
Uncalibrated Photometric Stereo for Unknown Isotropic Reflectances
We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances.
Bayesian Depth-from-Defocus with Shading Constraints
We present a method that enhances the performance of depth-from-defocus (DFD) through the use of shading information.
