Christopher Zach
Showing 36 publications
Text Prompt Augmentation for Zero-shot Out-of-Distribution Detection
Making Rotation Averaging Fast and Robust with Anisotropic Coordinate Descent
Text in the dark: Extremely low-light text image enhancement
Certifiably Optimal Anisotropic Rotation Averaging
When IC meets text: Towards a rich annotated integrated circuit text dataset
Deep Nearest Neighbors for Anomaly Detection in Chest X-Rays
Two Tales of Single-Phase Contrastive Hebbian Learning
Dyadic Learning in Recurrent and Feedforward Models
Learned Trajectory Embedding for Subspace Clustering
Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps,
Fully Variational Noise-Contrastive Estimation
Deep-learning-based out-of-distribution data detection in visual inspection images
Cycle-Object Consistency for Image-to-Image Domain Adaptation
GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons
Data Augmentation via Neural-Style-Transfer for Driver Distraction Recognition
Extremely Low-light Image Enhancement with Scene Text Restoration
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks
Effortless Training of Joint Energy-Based Models with Sliced Score Matching
CyEDA : CYCLE OBJECT EDGE CONSISTENCY DOMAIN ADAPTATION
Industrial X-ray Image Analysis with Deep Neural Networks Robust to Unexpected Input Data
Joint Energy-based Model for Deep Probabilistic Regression
Analysis of industrial X-ray computed tomography data with deep neural networks
Robust Fitting with Truncated Least Squares: A Bilevel Optimization Approach
Progressive Batching for Efficient Non-linear Least Squares
BabelCalib: A Universal Approach to Calibrating Central Cameras
AUTOENCODER-BASED ANOMALY DETECTION IN INDUSTRIAL X-RAY IMAGES
Contrastive learning for lifted networks
SG-VAE: Scene Grammar Variational Autoencoder to Generate New Indoor Scenes
A Graduated Filter Method for Large Scale Robust Estimation
Lifted Regression/Reconstruction Networks
Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions
Pareto meets huber: Efficiently avoiding poor minima in robust estimation
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Showing 4 research projects
Learning and Leveraging Rich Priors for Factorization Problems
Energy-based models for supervised deep neural networks and their applications
AI for Analysis for Naturalistic Driving Data
Automatic data analysis within non-destructive evaluation (ADA-NDE)