Search Results for author:
Found 51 papers, 10 papers with code
Towards Precise Completion of Deformable Shapes
Here, we claim that observing part of an object which was previously acquired as a whole, one could deal with both partial matching and shape completion in a holistic manner.
Surface Reconstruction from Gaussian Splatting via Novel Stereo Views
We propose a novel approach for surface reconstruction from Gaussian splatting models.
On Partial Shape Correspondence and Functional Maps
Our study of functional maps led us to a novel method that establishes direct correspondence between partial and full shapes through feature matching bypassing the need for functional map intermediate spaces.
FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions
Our proposed method, FuseCap, fuses the outputs of such vision experts with the original captions using a large language model (LLM), yielding comprehensive image descriptions.
Ranked #1 on
Image Captioning
on COCO Captions
(CLIPScore metric)
Learning Differential Invariants of Planar Curves
We evaluate our models qualitatively and quantitatively and propose a benchmark dataset to evaluate approximation models of differential invariants of planar curves.
Partial Shape Similarity via Alignment of Multi-Metric Hamiltonian Spectra
Matching similar regions is formulated as the alignment of the spectra of operators closely related to the Laplace-Beltrami operator (LBO).
Garment Avatars: Realistic Cloth Driving using Pattern Registration
Here, we propose an end-to-end pipeline for building drivable representations for clothing.
Elastica Models for Color Image Regularization
Recently, the authors proposed a color elastica model, which minimizes both the surface area and elastica of the image manifold.
Deep Signatures -- Learning Invariants of Planar Curves
We compare the proposed schemes to alternative state-of-the-art axiomatic constructions of group invariant arc-lengths and curvatures.
Depth Refinement for Improved Stereo Reconstruction
To mitigate this quadratic relation, we propose a simple but effective method that uses a refinement network for depth estimation.
Unsupervised High-Fidelity Facial Texture Generation and Reconstruction
In this paper, we propose a novel unified pipeline for both tasks, generation of both geometry and texture, and recovery of high-fidelity texture.
Multimodal Colored Point Cloud to Image Alignment
To overcome this difficulty, we consider a differential optimization method that aligns a colored point cloud with a given color image through iterative geometric and color matching.
U-mesh: Human Correspondence Matching with Mesh Convolutional Networks
Modeling correspondence as Euclidean proximity enables efficient optimization, both for network training and for the next step of the algorithm.
Provably Approximated ICP
A harder version is the \emph{registration problem}, where the correspondence is unknown, and the minimum is also over all possible correspondence functions from $P$ to $Q$.
Provably Approximated Point Cloud Registration
A harder version is the registration problem, where the correspondence is unknown, and the minimum is also over all possible correspondence functions from P to Q. Algorithms such as the Iterative Closest Point (ICP) and its variants were suggested for these problems, but none yield a provable non-trivial approximation for the global optimum.
Abiotic Stress Prediction from RGB-T Images of Banana Plantlets
Prediction of stress conditions is important for monitoring plant growth stages, disease detection, and assessment of crop yields.
A Color Elastica Model for Vector-Valued Image Regularization
Here, we introduce an addition to the Polyakov action for color images that minimizes the color manifold curvature.
LIMP: Learning Latent Shape Representations with Metric Preservation Priors
In this paper, we advocate the adoption of metric preservation as a powerful prior for learning latent representations of deformable 3D shapes.
Do We Need Depth in State-Of-The-Art Face Authentication?
The raw face stereo images along with the location in the image from which the face is extracted allow the proposed CNN to improve the recognition task while avoiding the need to explicitly handle the geometric structure of the face.
The Whole Is Greater Than the Sum of Its Nonrigid Parts
Here, we claim that observing part of an object which was previously acquired as a whole, one could deal with both partial matching and shape completion in a holistic manner.
Bilateral Operators for Functional Maps
In this paper, we develop a functional map framework for the shape correspondence problem by constructing pairwise constraints using point-wise descriptors.
Data Augmentation for Leaf Segmentation and Counting Tasks in Rosette Plants
Deep learning techniques involving image processing and data analysis are constantly evolving.
Deep Eikonal Solvers
A deep learning approach to numerically approximate the solution to the Eikonal equation is introduced.
Learning to Optimize Multigrid PDE Solvers
Constructing fast numerical solvers for partial differential equations (PDEs) is crucial for many scientific disciplines.
Synthesizing facial photometries and corresponding geometries using generative adversarial networks
We circumvent the parametrization issue by imposing a global mapping from our data to the unit rectangle.
Momen(e)t: Flavor the Moments in Learning to Classify Shapes
A fundamental question in learning to classify 3D shapes is how to treat the data in a way that would allow us to construct efficient and accurate geometric processing and analysis procedures.
Self-supervised Learning of Dense Shape Correspondence
The resulting learning model is class-agnostic, and is able to leverage any type of deformable geometric data for the training phase.
High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networks
A GAN is employed in order to imitate the space of parametrized human textures, while corresponding facial geometries are generated by learning the best 3DMM coefficients for each texture.
Computational Geometry
Specular-to-Diffuse Translation for Multi-View Reconstruction
To alleviate this restriction, we introduce S2Dnet, a generative adversarial network for transferring multiple views of objects with specular reflection into diffuse ones, so that multi-view reconstruction methods can be applied more effectively.
Parametric Manifold Learning Via Sparse Multidimensional Scaling
We propose a metric-learning framework for computing distance-preserving maps that generate low-dimensional embeddings for a certain class of manifolds.
DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling
This paper explores a fully unsupervised deep learning approach for computing distance-preserving maps that generate low-dimensional embeddings for a certain class of manifolds.
CoBe -- Coded Beacons for Localization, Object Tracking, and SLAM Augmentation
This paper presents a novel beacon light coding protocol, which enables fast and accurate identification of the beacons in an image.
Efficient Deformable Shape Correspondence via Kernel Matching
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality.
Sparse Approximation of 3D Meshes using the Spectral Geometry of the Hamiltonian Operator
Here, we incorporate the order of vertices into an operator that defines a novel spectral domain.
A Deep Learning Perspective on the Origin of Facial Expressions
Facial expressions play a significant role in human communication and behavior.
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
It has been recently shown that neural networks can recover the geometric structure of a face from a single given image.
Deep Stereo Matching with Dense CRF Priors
Stereo reconstruction from rectified images has recently been revisited within the context of deep learning.
Learning Invariant Representations Of Planar Curves
We propose a metric learning framework for the construction of invariant geometric functions of planar curves for the Eucledian and Similarity group of transformations.
Learning Detailed Face Reconstruction from a Single Image
In contrast, we propose to leverage the power of convolutional neural networks to produce a highly detailed face reconstruction from a single image.
Hamiltonian operator for spectral shape analysis
Many shape analysis methods treat the geometry of an object as a metric space that can be captured by the Laplace-Beltrami operator.
Customized Facial Constant Positive Air Pressure (CPAP) Masks
The incompatibility is characterized by gaps between the mask and the face, which deteriorates the impermeability of the mask and leads to air leakage.
Randomized Independent Component Analysis
Independent component analysis (ICA) is a method for recovering statistically independent signals from observations of unknown linear combinations of the sources.
Consistent Discretization and Minimization of the L1 Norm on Manifolds
The L1 norm has been tremendously popular in signal and image processing in the past two decades due to its sparsity-promoting properties.
3D Face Reconstruction by Learning from Synthetic Data
Fast and robust three-dimensional reconstruction of facial geometric structure from a single image is a challenging task with numerous applications.
Classical Scaling Revisited
We present an efficient solver for Classical Scaling (a specific MDS model) by extending the distances measured from a subset of the points to the rest, while exploiting the smoothness property of the distance functions.
Real-Time Depth Refinement for Specular Objects
The introduction of consumer RGB-D scanners set off a major boost in 3D computer vision research.
Rule Of Thumb: Deep derotation for improved fingertip detection
We investigate a novel global orientation regression approach for articulated objects using a deep convolutional neural network.
RGBD-Fusion: Real-Time High Precision Depth Recovery
The popularity of low-cost RGB-D scanners is increasing on a daily basis.
On the optimality of shape and data representation in the spectral domain
This novel pseudo-metric allows constructing an LBO by which a scale invariant eigenspace on the surface is defined.
Graph matching: relax or not?
We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement.
On Nonrigid Shape Similarity and Correspondence
An important operation in geometry processing is finding the correspondences between pairs of shapes.
