Christopher Zach

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

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

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

Learned Trajectory Embedding for Subspace Clustering

Deep Nearest Neighbors for Anomaly Detection in Chest X-Rays

Two Tales of Single-Phase Contrastive Hebbian Learning

Fully Variational Noise-Contrastive Estimation

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

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

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

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

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

Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons

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

Extremely Low-light Image Enhancement with Scene Text Restoration

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

CyEDA : CYCLE OBJECT EDGE CONSISTENCY DOMAIN ADAPTATION

2022

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

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

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

Joint Energy-based Model for Deep Probabilistic Regression

Robust Fitting with Truncated Least Squares: A Bilevel Optimization Approach

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

AUTOENCODER-BASED ANOMALY DETECTION IN INDUSTRIAL X-RAY IMAGES

Progressive Batching for Efficient Non-linear Least Squares

2021

BabelCalib: A Universal Approach to Calibrating Central Cameras

Contrastive learning for lifted networks

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

2020

Lifted Regression/Reconstruction Networks

A Graduated Filter Method for Large Scale Robust Estimation

2020

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

Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions

Pareto meets huber: Efficiently avoiding poor minima in robust estimation