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Open Set Learning

Traditional supervised learning aims to train a classifier in the closed-set world, where training and test samples share the same label space. Open set learning (OSL) is a more challenging and realistic setting, where there exist test samples from the classes that are unseen during training. Open set recognition (OSR) is the sub-task of detecting test samples which do not come from the training.

Papers

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Showing 201–225 of 267 papers

TitleStatusHype
Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition—0
Feature-Space Semantic Invariance: Enhanced OOD Detection for Open-Set Domain Generalization—0
FedPD: Federated Open Set Recognition with Parameter Disentanglement—0
Few-shot Open-set Recognition Using Background as Unknowns—0
From Coarse to Fine-Grained Open-Set Recognition—0
FSOS-AMC: Few-Shot Open-Set Learning for Automatic Modulation Classification—0
Gallery-Aware Uncertainty Estimation For Open-Set Face Recognition—0
Generalizing Cross Entropy Loss with a Beta Proper Composite Loss: An Improved Loss Function for Open Set Recognition—0
Generative-Discriminative Feature Representations for Open-Set Recognition—0
G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition—0
Hierarchical Models: Intrinsic Separability in High Dimensions—0
Hybrid Models for Open Set Recognition—0
Hyperbolic Dual Feature Augmentation for Open-Environment—0
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection—0
Individual common dolphin identification via metric embedding learning—0
Informed Decision-Making through Advancements in Open Set Recognition and Unknown Sample Detection—0
Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation—0
Open-set learning with augmented categories by exploiting unlabelled data—0
Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders—0
Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition—0
Know Yourself Better: Diverse Discriminative Feature Learning Improves Open Set Recognition—0
Latent Cognizance: What Machine Really Learns—0
Latent Space Energy-based Model for Fine-grained Open Set Recognition—0
Reconstruction guided Meta-learning for Few Shot Open Set Recognition—0
Learning for Transductive Threshold Calibration in Open-World Recognition—0
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