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Domain Generalization

1760 directly classified papers

Papers per year

Papers

CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth CVPR 2019
SpaceNet MVOI: A Multi-View Overhead Imagery Dataset ICCV 2019
Do Better ImageNet Models Transfer Better? CVPR 2019
Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data ICCV 2019
DLOW: Domain Flow for Adaptation and Generalization CVPR 2019
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers NIPS 2019
Robust Semantic Parsing with Adversarial Learning for Domain Generalization NAACL 2019
Generalizable Person Re-Identification by Domain-Invariant Mapping Network CVPR 2019
DIViS: Domain Invariant Visual Servoing for Collision-Free Goal Reaching RSS 2019
Exploring the Landscape of Spatial Robustness ICML 2019
Domain-agnostic Question-Answering with Adversarial Training EMNLP 2019
Addressing Model Vulnerability to Distributional Shifts Over Image Transformation Sets ICCV 2019
Comprehensive Multi-Dataset Evaluation of Reading Comprehension EMNLP 2019
DeRPN: Taking a Further Step toward More General Object Detection AAAI 2019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation EMNLP 2019
Generalizing Eye Tracking With Bayesian Adversarial Learning CVPR 2019
Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout NAACL 2019
Robustness of Statistical Voice Conversion Based on Direct Waveform Modification Against Background Sounds INTERSPEECH 2019
Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber's $M$-estimator NIPS 2019
Don’t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases IJCNLP 2019
Domain Generalization via Multidomain Discriminant Analysis UAI 2019
Adversarial Training and Robustness for Multiple Perturbations NIPS 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift NIPS 2019
Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set EMNLP 2019
Don’t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases EMNLP 2019