Christopher Zach

Forskningsprofessor vid Signalbehandling och medicinsk teknik

Christopher Zach är forskningsprofessor i forskargruppen Digitala bildsystem och bildanalys.

Källa: chalmers.se
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Visar 33 publikationer

2025

Text in the dark: Extremely low-light text image enhancement

Che-Tsung Lin, Chun Chet Ng, Zhi Qin Tan et al
Signal Processing: Image Communication. Vol. 130
Artikel i vetenskaplig tidskrift
2024

When IC meets text: Towards a rich annotated integrated circuit text dataset

Chun Chet Ng, Che-Tsung Lin, Zhi Qin Tan et al
Pattern Recognition. Vol. 147
Artikel i vetenskaplig tidskrift
2024

Text Prompt Augmentation for Zero-shot Out-of-Distribution Detection

Xixi Liu, Christopher Zach
2024 European Conference on Computer Vision. Vol. 15059-15147
Paper i proceeding
2024

Deep Nearest Neighbors for Anomaly Detection in Chest X-Rays

Xixi Liu, Jennifer Alvén, Ida Häggström et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 14349 LNCS, p. 293-302
Paper i proceeding
2024

Two Tales of Single-Phase Contrastive Hebbian Learning

Rasmus Kjær Høier, Christopher Zach
Proceedings of Machine Learning Research. Vol. 235, p. 18470-18488
Paper i proceeding
2024

Learned Trajectory Embedding for Subspace Clustering

Yaroslava Lochman, Carl Olsson, Christopher Zach
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 19092-19102
Paper i proceeding
2023

Fully Variational Noise-Contrastive Estimation

Christopher Zach
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 13886 LNCS, p. 175-190
Paper i proceeding
2023

Cycle-Object Consistency for Image-to-Image Domain Adaptation

Che-Tsung Lin, Jie Long Kew, Chee Seng Chan et al
Pattern Recognition. Vol. 138
Artikel i vetenskaplig tidskrift
2023

Rethinking Long-Tailed Visual Recognition with Dynamic Probability Smoothing and Frequency Weighted Focusing

Wan Jun Nah, Chun Chet Ng, Che-Tsung Lin et al
Proceedings - International Conference on Image Processing, ICIP, p. 435-439
Paper i proceeding
2023

Deep-learning-based out-of-distribution data detection in visual inspection images

Erik Lindgren, Christopher Zach
Proceedings of SPIE - The International Society for Optical Engineering. Vol. 12489
Paper i proceeding
2023

Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps,

Yadong Mao, Zhuqi Xiao, Che-Tsung Lin et al
IEEE Vehicular Technology Conference. Vol. 2023-June
Paper i proceeding
2023

Exploiting Redundancy for Large Scale Bundle Adjustment: In Partial Defense of Minimization by Alternation

Christopher Zach, Huu Le
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 13886 LNCS
Paper i proceeding
2023

Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons

Rasmus Kjær Høier, Dorian Staudt, Christopher Zach
Proceedings of Machine Learning Research. Vol. 202, p. 13141-13156
Paper i proceeding
2023

GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection

Xixi Liu, Yaroslava Lochman, Christopher Zach
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2023-June, p. 23946-23955
Paper i proceeding
2022

Extremely Low-light Image Enhancement with Scene Text Restoration

Pohao Hsu, Che-Tsung Lin, Chun Chet Ng et al
Proceedings - International Conference on Pattern Recognition. Vol. 2022-August, p. 317-323
Paper i proceeding
2022

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

Xixi Liu, Dorian Staudt, Che-Tsung Lin et al
Proceedings - International Conference on Pattern Recognition. Vol. 2022-August, p. 2643-2649
Paper i proceeding
2022

CyEDA : CYCLE OBJECT EDGE CONSISTENCY DOMAIN ADAPTATION

Jing Chong Beh, Kam Woh Ng, Jie Long Kew et al
Proceedings - International Conference on Image Processing, ICIP, p. 2986-2990
Paper i proceeding
2022

Industrial X-ray Image Analysis with Deep Neural Networks Robust to Unexpected Input Data

Erik Lindgren, Christopher Zach
Metals. Vol. 12 (11)
Artikel i vetenskaplig tidskrift
2022

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

Huu Le, Rasmus Kjær Høier, Che-Tsung Lin et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2022-June, p. 460-469
Paper i proceeding
2022

Data Augmentation via Neural-Style-Transfer for Driver Distraction Recognition

Che-Tsung Lin, Thomas Streubel, Marco Dozza et al
The 8th International Conference on Driver Distraction and Inattention
Paper i proceeding
2022

Joint Energy-based Model for Deep Probabilistic Regression

Xixi Liu, Che-Tsung Lin, Christopher Zach
Proceedings - International Conference on Pattern Recognition. Vol. 2022-August, p. 2693-2699
Paper i 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 i 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 i 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 i proceeding
2021

Progressive Batching for Efficient Non-linear Least Squares

Huu Le, Christopher Zach, Edward Rosten et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12624 LNCS, p. 506-522
Paper i 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 i proceeding
2020

Contrastive learning for lifted networks

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

Lifted Regression/Reconstruction Networks

Rasmus Kjær Høier, Christopher Zach
31st British Machine Vision Conference, BMVC 2020
Paper i 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 i 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 i proceeding
2019

Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions

Pulak Purkait, Christopher Zach, Ian Reid
IEEE International Conference on Intelligent Robots and Systems, p. 1998-2005
Paper i 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 i proceeding

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Visar 4 forskningsprojekt

2020–

Learning and Leveraging Rich Priors for Factorization Problems

Christopher Zach Digitala bildsystem och bildanalys
Carl Olsson Digitala bildsystem och bildanalys
Wallenberg AI, Autonomous Systems and Software Program

3 publikationer finns
2020–2025

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

Morteza Haghir Chehreghani Data Science
Christopher Zach Digitala bildsystem och bildanalys
Chalmers AI-forskningscentrum (CHAIR)

1 publikation finns
2020–2022

AI for Analysis for Naturalistic Driving Data

Dag Wedelin Data Science
Christopher Zach Digitala bildsystem och bildanalys
Marco Dozza Olycksanalys och prevention
AoA Transport Funds
Chalmers AI-forskningscentrum (CHAIR)

2019–2022

Automatic data analysis within non-destructive evaluation (ADA-NDE)

Fredrik Kahl Datorseende och medicinsk bildanalys
Håkan Wirdelius Konstruktionsmaterial
Erik Lindgren Konstruktionsmaterial
Christopher Zach Datorseende och medicinsk bildanalys
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Det kan finnas fler projekt där Christopher Zach medverkar, men du måste vara inloggad som anställd på Chalmers för att kunna se dem.