Christopher Zach

Forskningsprofessor at Signal Processing and Biomedical Engineering

Christopher Zach is a research professor in the research group Computer vision and medical image analysis. His main research interests are 3D reconstruction from images and 3D image understanding. Further, he conducts research in efficient and real-time methods for computer vision and machine learning, and therefore he also explores underlying mathematical models and suitable numerical optimization methods.

Source: chalmers.se
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Showing 16 publications

2022

Extremely Low-light Image Enhancement with Scene Text Restoration

Pohao Hsu, Che-Tsung Lin, Chun Chet Ng et al
International Conference on Pattern Recognition
Paper in proceeding
2022

Effortless Training of Joint Energy-Based Models with Sliced Score Matching

Xixi Liu, Dorian Staudt, Che-Tsung Lin et al
International Conference on Pattern Recognition
Paper in proceeding
2022

Joint Energy-based Model for Deep Probabilistic Regression

Xixi Liu, Che-Tsung Lin, Christopher Zach
International Conference on Pattern Recognition
Paper in proceeding
2022

AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks

Huu Le, Rasmus Kjær Høier, Che-Tsung Lin et al
CVPR 2022
Paper in proceeding
2021

BabelCalib: A Universal Approach to Calibrating Central Cameras

Yaroslava Lochman, Kostiantyn Liepieshov, Jianhui Chen et al
Proceedings of the IEEE International Conference on Computer Vision, p. 15233-15242
Paper in proceeding
2021

Progressive Batching for Efficient Non-linear Least Squares

Huu Le, Christopher Zach, Edward Rosten et al
Lecture Notes in Computer Science. Vol. 12624 LNCS, p. 506-522
Paper in proceeding
2021

AUTOENCODER-BASED ANOMALY DETECTION IN INDUSTRIAL X-RAY IMAGES

Erik Lindgren, Christopher Zach
Proceedings of 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, QNDE 2021
Paper in proceeding
2021

Robust Fitting with Truncated Least Squares: A Bilevel Optimization Approach

Huu Le, Christopher Zach
Proceedings - 2021 International Conference on 3D Vision, 3DV 2021, p. 1392-1400
Paper in proceeding
2021

Analysis of industrial X-ray computed tomography data with deep neural networks

Erik Lindgren, Christopher Zach
Proceedings of SPIE - The International Society for Optical Engineering. Vol. 11840
Paper in proceeding
2020

SG-VAE: Scene Grammar Variational Autoencoder to Generate New Indoor Scenes

Pulak Purkait, Christopher Zach, Ian Reid
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12369 LNCS, p. 155-171
Paper in proceeding
2020

Contrastive learning for lifted networks

Christopher Zach, Virginia Estellers
30th British Machine Vision Conference 2019, BMVC 2019
Paper in proceeding
2020

Lifted Regression/Reconstruction Networks

Rasmus Kjær Høier, Christopher Zach
31st British Machine Vison Conference 2020, BMVC 2020
Paper in proceeding
2020

A Graduated Filter Method for Large Scale Robust Estimation

Huu Le, Christopher Zach
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 5558-5567
Paper in proceeding
2020

Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning

Christopher Zach, Huu Le
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12371 LNCS, p. 464-480
Paper in proceeding
2019

Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions

Pulak Purkait, Christopher Zach, Ian Reid
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), p. 1998-2005
Paper in proceeding
2019

Pareto meets huber: Efficiently avoiding poor minima in robust estimation

Christopher Zach, Guillaume Bourmaud
Proceedings of the IEEE International Conference on Computer Vision. Vol. 2019-October, p. 10242-10250
Paper in proceeding

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Showing 3 research projects

2020–

Learning and Leveraging Rich Priors for Factorization Problems

Christopher Zach Imaging and Image Analysis
Carl Olsson Imaging and Image Analysis
Wallenberg AI, Autonomous Systems and Software Program

2020–2025

Energy-based models for supervised deep neural networks and their applications

Christopher Zach Imaging and Image Analysis
Morteza Haghir Chehreghani Data Science
Chalmers AI Research Centre (CHAIR)
Chalmers AI Research Centre

2020–2022

AI for Analysis for Naturalistic Driving Data

Christopher Zach Imaging and Image Analysis
Marco Dozza Crash Analysis and Prevention
Dag Wedelin Data Science
Chalmers AI Research Centre
AoA Transport Funds

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