mlsanityData to 7 Oct 2026

Generative OpenMax for Multi-Class Open Set Classification

arXiv 1707.07418 ↗First posted 24 Jul 2017cs.CVcited by 157

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Abstract (arXiv)

We present a conceptually new and flexible method for multi-class open set classification. Unlike previous methods where unknown classes are inferred with respect to the feature or decision distance to the known classes, our approach is able to provide explicit modelling and decision score for unknown classes. The proposed method, called Gener- ative OpenMax (G-OpenMax), extends OpenMax by employing generative adversarial networks (GANs) for novel category image synthesis. We validate the proposed method on two datasets of handwritten digits and characters, resulting in superior results over previous deep learning based method OpenMax Moreover, G-OpenMax provides a way to visualize samples representing the unknown classes from open space. Our simple and effective approach could serve as a new direction to tackle the challenging multi-class open set classification problem.

Key facts. Cited by 157 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jul 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 39; 2022: 43; 2023: 24; 2024: 25; 2025: 20; 2026: 6.

157 papers.

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  1. 2021Generalized Out-of-Distribution Detection: A Surveycited by 796
  2. 2021Open-Set Recognition: a Good Closed-Set Classifier is All You Need?cited by 351
  3. 2021Towards Open World Object Detectioncited by 297
  4. 2022OpenOOD: Benchmarking Generalized Out-of-Distribution Detectioncited by 267
  5. 2022Delving into Out-of-Distribution Detection with Vision-Language Representationscited by 215
  6. 2022Generalized Category Discoverycited by 209
  7. 2021Open-World Semi-Supervised Learningcited by 165
  8. 2023Towards Open Vocabulary Learning: A Surveycited by 165
  9. 2021A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challengescited by 154
  10. 2021Adversarial Reciprocal Points Learning for Open Set Recognitioncited by 153
  11. 2021Zero-Shot Out-of-Distribution Detection Based on the Pre-trained Model CLIPcited by 151
  12. 2021OpenGAN: Open-Set Recognition via Open Data Generationcited by 135
38 more
  1. 2021Learning Placeholders for Open-Set Recognitioncited by 121
  2. 2023LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learningcited by 107
  3. 2021Evidential Deep Learning for Open Set Action Recognitioncited by 96
  4. 2021Counterfactual Zero-Shot and Open-Set Visual Recognitioncited by 95
  5. 2022Harnessing Out-Of-Distribution Examples via Augmenting Content and Stylecited by 43
  6. 2023Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discoverycited by 39
  7. 2022Expanding Low-Density Latent Regions for Open-Set Object Detectioncited by 38
  8. 2023GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detectioncited by 36
  9. 2021One-Class Classification: A Surveycited by 35
  10. 2021Open-world Machine Learning: Applications, Challenges, and Opportunitiescited by 34
  11. 2024SelEx: Self-Expertise in Fine-Grained Generalized Category Discoverycited by 34
  12. 2022Active Learning for Open-set Annotationcited by 33
  13. 2022OpenAUC: Towards AUC-Oriented Open-Set Recognitioncited by 33
  14. 2023Progressive Open Space Expansion for Open-Set Model Attributioncited by 32
  15. 2021Few-shot Open-set Recognition by Transformation Consistencycited by 29
  16. 2021Learning Bounds for Open-Set Learningcited by 27
  17. 2022PMAL: Open Set Recognition via Robust Prototype Miningcited by 27
  18. 2021Uncertainty for Identifying Open-Set Errors in Visual Object Detectioncited by 26
  19. 2024A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practicecited by 26
  20. 2021A Survey on Open Set Recognitioncited by 25
  21. 2022Difficulty-Aware Simulator for Open Set Recognitioncited by 24
  22. 2023Generalizable Decision Boundaries: Dualistic Meta-Learning for Open Set Domain Generalizationcited by 24
  23. 2022OpenTAL: Towards Open Set Temporal Action Localizationcited by 23
  24. 2022Out-of-Distribution Detection with Semantic Mismatch under Maskingcited by 22
  25. 2023Entropic Open-set Active Learningcited by 22
  26. 2022Open-set Adversarial Defense with Clean-Adversarial Mutual Learningcited by 21
  27. 2024Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalizationcited by 20
  28. 2021A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networkscited by 19
  29. 2021Conditional Variational Capsule Network for Open Set Recognitioncited by 17
  30. 2022Your Out-of-Distribution Detection Method is Not Robust!cited by 16
  31. 2023CNS-Net: Conservative Novelty Synthesizing Network for Malware Recognition in an Open-set Scenariocited by 15
  32. 2021Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applicationscited by 14
  33. 2025Handling Out-of-Distribution Data: A Surveycited by 14
  34. 2024Gradient-Regularized Out-of-Distribution Detectioncited by 13
  35. 2024Dissecting Out-of-Distribution Detection and Open-Set Recognition: A Critical Analysis of Methods and Benchmarkscited by 13
  36. 2024Open World Object Detection: A Surveycited by 13
  37. 2021M2IOSR: Maximal Mutual Information Open Set Recognitioncited by 12
  38. 2022Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometrycited by 12

50 most cited of 157 All 157 (JSON)