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06/11/2021
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction
The impressive performance of deep convolutional neural networks in sing...
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03/15/2021
Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging
Under mild conditions on the noise level of the measurements, rotation a...
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12/02/2020
Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks
Image convolutions have been a cornerstone of a great number of deep lea...
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05/10/2020
A Simple and Scalable Shape Representation for 3D Reconstruction
Deep learning applied to the reconstruction of 3D shapes has seen growin...
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04/14/2020
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
The impressive performance of deep convolutional neural networks in sing...
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03/03/2020
Implicitly Defined Layers in Neural Networks
In conventional formulations of multilayer feedforward neural networks, ...
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02/11/2019
Visual SLAM: Why Bundle Adjust?
Bundle adjustment plays a vital role in feature-based monocular SLAM. In...
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02/05/2019
SASSE: Scalable and Adaptable 6-DOF Pose Estimation
Visual localization has become a key enabling component of many place re...
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01/21/2019
Deep Level Sets: Implicit Surface Representations for 3D Shape Inference
Existing 3D surface representation approaches are unable to accurately c...
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12/07/2018
Star Tracking using an Event Camera
Star trackers are primarily optical devices that are used to estimate th...
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10/24/2018
A Binary Optimization Approach for Constrained K-Means Clustering
K-Means clustering still plays an important role in many computer vision...
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09/21/2018
3D Move to See: Multi-perspective visual servoing for improving object views with semantic segmentation
In this paper, we present a new approach to visual servoing for robotics...
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03/29/2018
Learning Free-Form Deformations for 3D Object Reconstruction
Representing 3D shape in deep learning frameworks in an accurate, effici...
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03/22/2018
Maximum Consensus Parameter Estimation by Reweighted ℓ_1 Methods
Robust parameter estimation in computer vision is frequently accomplishe...
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11/29/2017
Image2Mesh: A Learning Framework for Single Image 3D Reconstruction
One challenge that remains open in 3D deep learning is how to efficientl...
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10/27/2017
Deterministic Approximate Methods for Maximum Consensus Robust Fitting
Maximum consensus estimation plays a critically important role in robust...
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07/23/2017
Compact Model Representation for 3D Reconstruction
3D reconstruction from 2D images is a central problem in computer vision...
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05/03/2017
Rotation Averaging and Strong Duality
In this paper we explore the role of duality principles within the probl...
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06/14/2016
Richardson-Lucy Deblurring for Moving Light Field Cameras
We generalize Richardson-Lucy (RL) deblurring to 4-D light fields by rep...
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03/16/2016