{"total":140,"rows":[{"id":"2110.11334","title":"Generalized Out-of-Distribution Detection: A Survey","created":"2021-10-21","cited_by_count":802,"area":null},{"id":"2103.12051","title":"SSD: A Unified Framework for Self-Supervised Outlier Detection","created":"2021-03-22","cited_by_count":264,"area":null},{"id":"2302.03648","title":"Class-Incremental Learning: A Survey","created":"2023-02-07","cited_by_count":209,"area":null},{"id":"2110.14051","title":"A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges","created":"2021-10-26","cited_by_count":154,"area":null},{"id":"2103.00887","title":"Counterfactual Zero-Shot and Open-Set Visual Recognition","created":"2021-03-01","cited_by_count":95,"area":null},{"id":"2104.03344","title":"OVANet: One-vs-All Network for Universal Domain Adaptation","created":"2021-04-07","cited_by_count":92,"area":null},{"id":"2203.02261","title":"Class-Aware Contrastive Semi-Supervised Learning","created":"2022-03-04","cited_by_count":62,"area":null},{"id":"2203.02194","title":"Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection","created":"2022-03-04","cited_by_count":59,"area":null},{"id":"2104.06601","title":"Zero-Shot Instance Segmentation","created":"2021-04-14","cited_by_count":40,"area":null},{"id":"2207.11455","title":"UC-OWOD: Unknown-Classified Open World Object Detection","created":"2022-07-23","cited_by_count":40,"area":null},{"id":"2310.19776","title":"Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery","created":"2023-10-30","cited_by_count":39,"area":null},{"id":"2112.01698","title":"Learning to Detect Every Thing in an Open World","created":"2021-12-03","cited_by_count":37,"area":null},{"id":"2105.13448","title":"Open-world Machine Learning: Applications, Challenges, and Opportunities","created":"2021-05-27","cited_by_count":34,"area":null},{"id":"2408.14371","title":"SelEx: Self-Expertise in Fine-Grained Generalized Category Discovery","created":"2024-08-26","cited_by_count":34,"area":null},{"id":"2210.13458","title":"OpenAUC: Towards AUC-Oriented Open-Set Recognition","created":"2022-10-22","cited_by_count":33,"area":null},{"id":"2303.06877","title":"Progressive Open Space Expansion for Open-Set Model Attribution","created":"2023-03-13","cited_by_count":32,"area":null},{"id":"2207.02158","title":"Class-Specific Semantic Reconstruction for Open Set Recognition","created":"2022-07-05","cited_by_count":28,"area":null},{"id":"2102.05897","title":"Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approaches","created":"2021-02-11","cited_by_count":27,"area":null},{"id":"2106.15792","title":"Learning Bounds for Open-Set Learning","created":"2021-06-30","cited_by_count":27,"area":null},{"id":"2203.08569","title":"PMAL: Open Set Recognition via Robust Prototype Mining","created":"2022-03-16","cited_by_count":27,"area":null},{"id":"2104.01328","title":"Uncertainty for Identifying Open-Set Errors in Visual Object Detection","created":"2021-04-03","cited_by_count":26,"area":null},{"id":"2109.00893","title":"A Survey on Open Set Recognition","created":"2021-08-18","cited_by_count":25,"area":null},{"id":"2210.04137","title":"Few-Shot Continual Active Learning by a Robot","created":"2022-10-09","cited_by_count":25,"area":null},{"id":"2207.10024","title":"Difficulty-Aware Simulator for Open Set Recognition","created":"2022-07-20","cited_by_count":24,"area":null},{"id":"2308.09391","title":"Generalizable Decision Boundaries: Dualistic Meta-Learning for Open Set Domain Generalization","created":"2023-08-18","cited_by_count":24,"area":null},{"id":"2203.05114","title":"OpenTAL: Towards Open Set Temporal Action Localization","created":"2022-03-10","cited_by_count":23,"area":null},{"id":"2312.14126","title":"Entropic Open-set Active Learning","created":"2023-12-21","cited_by_count":23,"area":null},{"id":"2202.05953","title":"Open-set Adversarial Defense with Clean-Adversarial Mutual Learning","created":"2022-02-12","cited_by_count":21,"area":null},{"id":"2110.04514","title":"Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach","created":"2021-10-09","cited_by_count":20,"area":null},{"id":"2404.00710","title":"Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization","created":"2024-03-31","cited_by_count":20,"area":null},{"id":"2104.09159","title":"Conditional Variational Capsule Network for Open Set Recognition","created":"2021-04-19","cited_by_count":17,"area":null},{"id":"2210.15909","title":"Subsidiary Prototype Alignment for Universal Domain Adaptation","created":"2022-10-28","cited_by_count":17,"area":null},{"id":"2312.06330","title":"Navigating Open Set Scenarios for Skeleton-based Action Recognition","created":"2023-12-11","cited_by_count":17,"area":null},{"id":"2104.03182","title":"Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications","created":"2021-04-07","cited_by_count":14,"area":null},{"id":"2108.06024","title":"CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue","created":"2021-08-13","cited_by_count":14,"area":null},{"id":"2204.02553","title":"RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection","created":"2022-04-06","cited_by_count":13,"area":null},{"id":"2410.11301","title":"Open World Object Detection: A Survey","created":"2024-10-15","cited_by_count":13,"area":null},{"id":"2108.02373","title":"M2IOSR: Maximal Mutual Information Open Set Recognition","created":"2021-08-05","cited_by_count":12,"area":null},{"id":"2207.09963","title":"Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry","created":"2022-07-20","cited_by_count":12,"area":null},{"id":"2309.01265","title":"SOAR: Scene-debiasing Open-set Action Recognition","created":"2023-09-03","cited_by_count":12,"area":null},{"id":"2407.16133","title":"Open-Set Biometrics: Beyond Good Closed-Set Models","created":"2024-07-23","cited_by_count":12,"area":null},{"id":"2409.17555","title":"Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler","created":"2024-09-26","cited_by_count":12,"area":null},{"id":"2206.09358","title":"What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs","created":"2022-06-19","cited_by_count":11,"area":null},{"id":"2103.10230","title":"Collective Decision of One-vs-Rest Networks for Open Set Recognition","created":"2021-03-18","cited_by_count":10,"area":null},{"id":"2206.15186","title":"Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images","created":"2022-06-30","cited_by_count":10,"area":null},{"id":"2207.10287","title":"Towards Accurate Open-Set Recognition via Background-Class Regularization","created":"2022-07-21","cited_by_count":10,"area":null},{"id":"2309.12780","title":"LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition","created":"2023-09-22","cited_by_count":10,"area":null},{"id":"2207.02504","title":"Dual Decision Improves Open-Set Panoptic Segmentation","created":"2022-07-06","cited_by_count":9,"area":null},{"id":"2311.13355","title":"Unified Classification and Rejection: A One-versus-All Framework","created":"2023-11-22","cited_by_count":9,"area":null},{"id":"2401.06521","title":"Exploring Diverse Representations for Open Set Recognition","created":"2024-01-12","cited_by_count":8,"area":null},{"id":"2409.14273","title":"Lidar Panoptic Segmentation in an Open World","created":"2024-09-22","cited_by_count":8,"area":null},{"id":"2206.08229","title":"Open-Set Recognition with Gradient-Based Representations","created":"2022-06-16","cited_by_count":7,"area":null},{"id":"2206.13691","title":"Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spotting","created":"2022-06-28","cited_by_count":7,"area":null},{"id":"2209.03519","title":"Measuring Human Perception to Improve Open Set Recognition","created":"2022-09-08","cited_by_count":7,"area":null},{"id":"2304.13349","title":"Discrepancy-Guided Reconstruction Learning for Image Forgery Detection","created":"2023-04-26","cited_by_count":7,"area":null},{"id":"2312.15571","title":"A Survey on Open-Set Image Recognition","created":"2023-12-25","cited_by_count":7,"area":null},{"id":"2402.06985","title":"OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery","created":"2024-02-10","cited_by_count":7,"area":null},{"id":"2206.04242","title":"OOD Augmentation May Be at Odds with Open-Set Recognition","created":"2022-06-09","cited_by_count":6,"area":null},{"id":"2207.09059","title":"Few-shot Open-set Recognition Using Background as Unknowns","created":"2022-07-19","cited_by_count":6,"area":null},{"id":"2304.05212","title":"Open Set Classification of GAN-based Image Manipulations via a ViT-based Hybrid Architecture","created":"2023-04-11","cited_by_count":6,"area":null},{"id":"2309.07403","title":"Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorance","created":"2023-09-14","cited_by_count":6,"area":null},{"id":"2405.11491","title":"BOSC: A Backdoor-based Framework for Open Set Synthetic Image Attribution","created":"2024-05-19","cited_by_count":6,"area":null},{"id":"2412.18342","title":"Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization","created":"2024-12-24","cited_by_count":6,"area":null},{"id":"2506.13265","title":"Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning","created":"2025-06-16","cited_by_count":6,"area":null},{"id":"2108.09199","title":"An Adaptable Deep Learning-Based Intrusion Detection System to Zero-Day Attacks","created":"2021-08-20","cited_by_count":5,"area":null},{"id":"2209.12935","title":"A Comprehensive Review of Trends, Applications and Challenges In Out-of-Distribution Detection","created":"2022-09-26","cited_by_count":5,"area":null},{"id":"2108.04225","title":"Adversarial Motorial Prototype Framework for Open Set Recognition","created":"2021-07-13","cited_by_count":4,"area":null},{"id":"2105.07635","title":"Open-set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios","created":"2021-05-17","cited_by_count":3,"area":null},{"id":"2310.09761","title":"CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes","created":"2023-10-15","cited_by_count":3,"area":null},{"id":"2401.17654","title":"All Beings Are Equal in Open Set Recognition","created":"2024-01-31","cited_by_count":3,"area":null},{"id":"2503.17717","title":"BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors","created":"2025-03-22","cited_by_count":3,"area":null},{"id":"2510.13037","title":"Conformal Inference for Open-Set and Imbalanced Classification","created":"2025-10-14","cited_by_count":3,"area":null},{"id":"2105.10013","title":"Opening Deep Neural Networks with Generative Models","created":"2021-05-20","cited_by_count":2,"area":null},{"id":"2105.13557","title":"Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition","created":"2021-05-28","cited_by_count":2,"area":null},{"id":"2110.11013","title":"Spatial Location Constraint Prototype Loss for Open Set Recognition","created":"2021-10-21","cited_by_count":2,"area":null},{"id":"2201.02923","title":"Open-Set Recognition of Breast Cancer Treatments","created":"2022-01-09","cited_by_count":2,"area":null},{"id":"2205.07466","title":"Robust Representation via Dynamic Feature Aggregation","created":"2022-05-16","cited_by_count":2,"area":null},{"id":"2208.06809","title":"Multi-Attribute Open Set Recognition","created":"2022-08-14","cited_by_count":2,"area":null},{"id":"2208.14071","title":"Deep Open-Set Recognition for Silicon Wafer Production Monitoring","created":"2022-08-30","cited_by_count":2,"area":null},{"id":"2209.11436","title":"Understanding Open-Set Recognition by Jacobian Norm and Inter-Class Separation","created":"2022-09-23","cited_by_count":2,"area":null},{"id":"2211.10872","title":"MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration","created":"2022-11-20","cited_by_count":2,"area":null},{"id":"2212.11747","title":"Deep Simplex Classifier for Maximizing the Margin in Both Euclidean and Angular Spaces","created":"2022-12-22","cited_by_count":2,"area":null},{"id":"2303.05122","title":"M-Tuning: Prompt Tuning with Mitigated Label Bias in Open-Set Scenarios","created":"2023-03-09","cited_by_count":2,"area":null},{"id":"2306.01222","title":"Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2308.12584","title":"LORD: Leveraging Open-Set Recognition with Unknown Data","created":"2023-08-24","cited_by_count":2,"area":null},{"id":"2309.10711","title":"Latent Space Energy-based Model for Fine-grained Open Set Recognition","created":"2023-09-19","cited_by_count":2,"area":null},{"id":"2403.02637","title":"BSDP: Brain-inspired Streaming Dual-level Perturbations for Online Open World Object Detection","created":"2024-03-05","cited_by_count":2,"area":null},{"id":"2412.09229","title":"UADet: A Remarkably Simple Yet Effective Uncertainty-Aware Open-Set Object Detection Framework","created":"2024-12-12","cited_by_count":2,"area":null},{"id":"2511.08196","title":"UCDSC: Open Set UnCertainty aware Deep Simplex Classifier for Medical Image Datasets","created":"2025-11-11","cited_by_count":2,"area":null},{"id":"2107.06668","title":"Thinkback: Task-SpecificOut-of-Distribution Detection","created":"2021-07-13","cited_by_count":1,"area":null},{"id":"2109.06859","title":"One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set Classification","created":"2021-09-14","cited_by_count":1,"area":null},{"id":"2111.08062","title":"Synthetic Unknown Class Learning for Learning Unknowns","created":"2021-11-15","cited_by_count":1,"area":null},{"id":"2205.07160","title":"Evaluating Uncertainty Calibration for Open-Set Recognition","created":"2022-05-15","cited_by_count":1,"area":null},{"id":"2207.09775","title":"Rethinking Open-Set Object Detection: Issues, a New Formulation, and Taxonomy","created":"2022-07-20","cited_by_count":1,"area":null},{"id":"2208.10489","title":"Audio Deepfake Attribution: An Initial Dataset and Investigation","created":"2022-08-21","cited_by_count":1,"area":null},{"id":"2303.01559","title":"Improving GAN Training via Feature Space Shrinkage","created":"2023-03-02","cited_by_count":1,"area":null},{"id":"2306.13895","title":"Open-Set RF Fingerprinting via Improved Prototype Learning","created":"2023-06-24","cited_by_count":1,"area":null},{"id":"2402.06331","title":"Taking Class Imbalance Into Account in Open Set Recognition Evaluation","created":"2024-02-09","cited_by_count":1,"area":null},{"id":"2404.17830","title":"Dynamic Against Dynamic: An Open-set Self-learning Framework","created":"2024-04-27","cited_by_count":1,"area":null},{"id":"2405.16368","title":"Qsco: A Quantum Scoring Module for Open-set Supervised Anomaly Detection","created":"2024-05-25","cited_by_count":1,"area":null}],"next_cursor":"100"}