mlsanityData to 7 Oct 2026

Heterogeneous Domain Generalization via Domain Mixup

arXiv 2009.05448 ↗First posted 11 Sep 2020cs.CVcited by 103

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Abstract (arXiv)

One of the main drawbacks of deep Convolutional Neural Networks (DCNN) is that they lack generalization capability. In this work, we focus on the problem of heterogeneous domain generalization which aims to improve the generalization capability across different tasks, which is, how to learn a DCNN model with multiple domain data such that the trained feature extractor can be generalized to supporting recognition of novel categories in a novel target domain. To solve this problem, we propose a novel heterogeneous domain generalization method by mixing up samples across multiple source domains with two different sampling strategies. Our experimental results based on the Visual Decathlon benchmark demonstrates the effectiveness of our proposed method. The code is released in urlhttps://github.com/wyf0912/MIXALL

Key facts. Cited by 103 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 25; 2022: 23; 2023: 29; 2024: 16; 2025: 7; 2026: 3.

103 papers.

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  1. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 762
  2. 2021Domain Generalization: A Surveycited by 760
  3. 2021SWAD: Domain Generalization by Seeking Flat Minimacited by 431
  4. 2022Improving Out-of-Distribution Robustness via Selective Augmentationcited by 202
  5. 2021SelfReg: Self-supervised Contrastive Regularization for Domain Generalizationcited by 189
  6. 2021Fishr: Invariant Gradient Variances for Out-of-Distribution Generalizationcited by 186
  7. 2021A Fine-Grained Analysis on Distribution Shiftcited by 171
  8. 2021Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalizationcited by 144
  9. 2022Domain Generalization by Mutual-Information Regularization with Pre-trained Modelscited by 133
  10. 2021Open Domain Generalization with Domain-Augmented Meta-Learningcited by 115
  11. 2021Model-Based Domain Generalizationcited by 103
  12. 2022Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understandingcited by 102
38 more
  1. 2021Exploiting Domain-Specific Features to Enhance Domain Generalizationcited by 86
  2. 2021On the Impact of Spurious Correlation for Out-of-distribution Detectioncited by 68
  3. 2021Adaptive Methods for Real-World Domain Generalizationcited by 66
  4. 2023Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detectioncited by 57
  5. 2022DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotationscited by 54
  6. 2022Prompt Vision Transformer for Domain Generalizationcited by 52
  7. 2023Leveraging Vision-Language Models for Improving Domain Generalization in Image Classificationcited by 41
  8. 2022Test-Time Robust Personalization for Federated Learningcited by 39
  9. 2023StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalizationcited by 36
  10. 2021Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directionscited by 35
  11. 2021Unsupervised Domain Generalization by Learning a Bridge Across Domainscited by 33
  12. 2022Grounding Visual Representations with Texts for Domain Generalizationcited by 30
  13. 2021Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillationcited by 28
  14. 2022Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognitioncited by 28
  15. 2024Domain Generalization through Meta-Learning: A Surveycited by 28
  16. 2023Flatness-Aware Minimization for Domain Generalizationcited by 27
  17. 2023What can a cook in Italy teach a mechanic in India? Action Recognition Generalisation Over Scenarios and Locationscited by 25
  18. 2023Out-of-Domain Robustness via Targeted Augmentationscited by 24
  19. 2023APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIPcited by 24
  20. 2022MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Taskcited by 23
  21. 2023Invariant Learning via Probability of Sufficient and Necessary Causescited by 22
  22. 2021Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanismscited by 20
  23. 2023DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networkscited by 20
  24. 2024Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalizationcited by 20
  25. 2022Localized Adversarial Domain Generalizationcited by 19
  26. 2021Variational Disentanglement for Domain Generalizationcited by 18
  27. 2023ERM++: An Improved Baseline for Domain Generalizationcited by 18
  28. 2023Temporal Coherent Test-Time Optimization for Robust Video Classificationcited by 15
  29. 2023Understanding Hessian Alignment for Domain Generalizationcited by 15
  30. 2023Improving Domain Generalization with Domain Relationscited by 14
  31. 2024HYPO: Hyperspherical Out-of-Distribution Generalizationcited by 13
  32. 2021Multi-Source domain adaptation via supervised contrastive learning and confident consistency regularizationcited by 12
  33. 2023Domain Generalization via Nuclear Norm Regularizationcited by 12
  34. 2023Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issuescited by 12
  35. 2024Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Schedulercited by 12
  36. 2021Out-of-Distribution Generalization Analysis via Influence Functioncited by 11
  37. 2021Towards Data-Free Domain Generalizationcited by 11
  38. 2022Adaptive Domain Generalization via Online Disagreement Minimizationcited by 9

50 most cited of 103 All 103 (JSON)