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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 1–50 of 267 papers

TitleStatusHype
Open-Set Image Tagging with Multi-Grained Text SupervisionCode4
Open World Object Detection: A SurveyCode2
Towards Open Vocabulary Learning: A SurveyCode2
Open-set Adversarial DefenseCode1
OpenGAN: Open-Set Recognition via Open Data GenerationCode1
Open-set recognition with long-tail sonar imagesCode1
Maximum Class Separation as Inductive Bias in One MatrixCode1
Glocal Energy-based Learning for Few-Shot Open-Set RecognitionCode1
Large-Scale Long-Tailed Recognition in an Open WorldCode1
Learning Placeholders for Open-Set RecognitionCode1
Navigating Open Set Scenarios for Skeleton-based Action RecognitionCode1
OpenGCD: Assisting Open World Recognition with Generalized Category DiscoveryCode1
Open-Set Automatic Target RecognitionCode1
Open Set Recognition using Vision Transformer with an Additional Detection HeadCode1
Few-Shot Open-Set Learning for On-Device Customization of KeyWord Spotting SystemsCode1
Driver Anomaly Detection: A Dataset and Contrastive Learning ApproachCode1
Fully Convolutional Open Set SegmentationCode1
GlanceNets: Interpretabile, Leak-proof Concept-based ModelsCode1
Adversarial Reciprocal Points Learning for Open Set RecognitionCode1
In or Out? Fixing ImageNet Out-of-Distribution Detection EvaluationCode1
Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open WorldsCode1
Learning Open Set Network with Discriminative Reciprocal PointsCode1
Difficulty-Aware Simulator for Open Set RecognitionCode1
OpenAUC: Towards AUC-Oriented Open-Set RecognitionCode1
A Unified Benchmark for the Unknown Detection Capability of Deep Neural NetworksCode1
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future ChallengesCode1
Open-set Adversarial Defense with Clean-Adversarial Mutual LearningCode1
BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background PriorsCode1
Open-Set Likelihood Maximization for Few-Shot LearningCode1
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?Code1
Domain Adaptive Few-Shot Open-Set LearningCode1
Evidential Deep Learning for Open Set Action RecognitionCode1
Exploring Diverse Representations for Open Set RecognitionCode1
Class Anchor Clustering: a Loss for Distance-based Open Set RecognitionCode1
Adversarial Motorial Prototype Framework for Open Set RecognitionCode1
Few-Shot Open-Set Recognition using Meta-LearningCode1
GDumb: A Simple Approach that Questions Our Progress in Continual LearningCode1
Generalized Out-of-Distribution Detection: A SurveyCode1
Few-shot Open-set Recognition by Transformation ConsistencyCode1
HomOpt: A Homotopy-Based Hyperparameter Optimization MethodCode1
Conditional Gaussian Distribution Learning for Open Set RecognitionCode1
Conditional Variational Capsule Network for Open Set RecognitionCode1
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set RecognitionCode1
COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous DrivingCode1
Counterfactual Zero-Shot and Open-Set Visual RecognitionCode1
Learning Bounds for Open-Set LearningCode1
Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity RecognitionCode1
Dissecting Out-of-Distribution Detection and Open-Set Recognition: A Critical Analysis of Methods and BenchmarksCode1
OneRing: A Simple Method for Source-free Open-partial Domain AdaptationCode1
Model-Agnostic Few-Shot Open-Set RecognitionCode1
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