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04/04/2023
Fully Variational Noise-Contrastive Estimation
By using the underlying theory of proper scoring rules, we design a fami...
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02/02/2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons
Activity difference based learning algorithms-such as contrastive Hebbia...
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04/01/2022
Extremely Low-light Image Enhancement with Scene Text Restoration
Deep learning-based methods have made impressive progress in enhancing e...
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12/06/2021
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks
We propose a new algorithm for training deep neural networks (DNNs) with...
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09/20/2021
BabelCalib: A Universal Approach to Calibrating Central Cameras
Existing calibration methods occasionally fail for large field-of-view c...
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05/15/2021
Bilevel Programming and Deep Learning: A Unifying View on Inference Learning Methods
In this work we unify a number of inference learning methods, that are p...
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02/22/2021
Escaping Poor Local Minima in Large Scale Robust Estimation
Robust parameter estimation is a crucial task in several 3D computer vis...
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10/21/2020
Progressive Batching for Efficient Non-linear Least Squares
Non-linear least squares solvers are used across a broad range of offlin...
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05/07/2020
Lifted Regression/Reconstruction Networks
In this work we propose lifted regression/reconstruction networks (LRRNs...
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03/20/2020
A Graduated Filter Method for Large Scale Robust Estimation
Due to the highly non-convex nature of large-scale robust parameter esti...
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03/12/2020
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning
Optimization problems with an auxiliary latent variable structure in add...
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12/10/2019
Learning to generate new indoor scenes
Deep generative models have been used in recent years to learn coherent ...
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06/19/2019
Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss
Three-dimensional object detection from a single view is a challenging t...
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06/07/2019
Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions
Semantic segmentation and instance level segmentation made substantial p...
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05/07/2019
Contrastive Learning for Lifted Networks
In this work we address supervised learning via lifted network formulati...
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08/10/2018
Weakly supervised learning of indoor geometry by dual warping
A major element of depth perception and 3D understanding is the ability ...
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05/11/2018
ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time
Modern deep learning architectures produce highly accurate results on ma...
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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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12/09/2017
SPP-Net: Deep Absolute Pose Regression with Synthetic Views
Image based localization is one of the important problems in computer vi...
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12/08/2017
Minimal Solvers for Monocular Rolling Shutter Compensation under Ackermann Motion
Modern automotive vehicles are often equipped with a budget commercial r...
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11/12/2014
Multi-modal Image Registration for Correlative Microscopy
Correlative microscopy is a methodology combining the functionality of l...
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08/14/2013