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Domain Adaptive Neural Networks for Object Recognition

arXiv 1409.6041 ↗First posted 21 Sep 2014cs.CV cs.AI cs.LGcited by 51

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Abstract (arXiv)

We propose a simple neural network model to deal with the domain adaptation problem in object recognition. Our model incorporates the Maximum Mean Discrepancy (MMD) measure as a regularization in the supervised learning to reduce the distribution mismatch between the source and target domains in the latent space. From experiments, we demonstrate that the MMD regularization is an effective tool to provide good domain adaptation models on both SURF features and raw image pixels of a particular image data set. We also show that our proposed model, preceded by the denoising auto-encoder pretraining, achieves better performance than recent benchmark models on the same data sets. This work represents the first study of MMD measure in the context of neural networks.

Key facts. Cited by 51 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Sep 2014.

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Citing papers per year: 2021: 19; 2022: 12; 2023: 8; 2024: 3; 2025: 8; 2026: 1.

51 papers.

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  1. 2022Understanding and Improving Visual Prompting: A Label-Mapping Perspectivecited by 86
  2. 2022Deep Clustering: A Comprehensive Surveycited by 78
  3. 2023Recent Advances in Optimal Transport for Machine Learningcited by 66
  4. 2021Federated Multi-Target Domain Adaptationcited by 44
  5. 2021Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safetycited by 35
  6. 2021A Survey of Unsupervised Domain Adaptation for Visual Recognitioncited by 31
  7. 2022Domain Adaptation for Time-Series Classification to Mitigate Covariate Shiftcited by 24
  8. 2021A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samplescited by 22
  9. 2021Towards Optimal Strategies for Training Self-Driving Perception Models in Simulationcited by 12
  10. 2021Deep Spherical Manifold Gaussian Kernel for Unsupervised Domain Adaptationcited by 9
  11. 2024From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarioscited by 9
  12. 2021Multi-source Few-shot Domain Adaptationcited by 7
38 more
  1. 2021Learning to Transfer for Traffic Forecasting via Multi-task Learningcited by 7
  2. 2022Angular Gap: Reducing the Uncertainty of Image Difficulty through Model Calibrationcited by 6
  3. 2022Jitter Does Matter: Adapting Gaze Estimation to New Domainscited by 6
  4. 2022Unsupervised Non-transferable Text Classificationcited by 6
  5. 2025Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classificationcited by 6
  6. 2021Efficient Pre-trained Features and Recurrent Pseudo-Labeling in Unsupervised Domain Adaptationcited by 4
  7. 2021Enhanced Separable Disentanglement for Unsupervised Domain Adaptationcited by 4
  8. 2022Exploring the Intersection between Neural Architecture Search and Continual Learningcited by 4
  9. 2022Gated Domain Units for Multi-source Domain Generalizationcited by 4
  10. 2022ModSelect: Automatic Modality Selection for Synthetic-to-Real Domain Generalizationcited by 4
  11. 2023Benchmarking Domain Adaptation for Chemical Processes on the Tennessee Eastman Processcited by 4
  12. 2023Robust and Communication-Efficient Federated Domain Adaptation via Random Featurescited by 4
  13. 2025STA-GANN: A Valid and Generalizable Spatio-Temporal Kriging Approachcited by 4
  14. 2021Adversarial Regression Learning for Bone Age Estimationcited by 3
  15. 2021Deep Least Squares Alignment for Unsupervised Domain Adaptationcited by 3
  16. 2022Physically-Based Face Rendering for NIR-VIS Face Recognitioncited by 3
  17. 2023Knowledge-inspired Subdomain Adaptation for Cross-Domain Knowledge Transfercited by 3
  18. 2024Optimal Transport for Domain Adaptation through Gaussian Mixture Modelscited by 3
  19. 2025On the geometry and topology of representations: the manifolds of modular additioncited by 3
  20. 2021Correlated Adversarial Joint Discrepancy Adaptation Networkcited by 2
  21. 2021Action Recognition with Domain Invariant Features of Skeleton Imagecited by 2
  22. 2025Using Kolmogorov-Smirnov Distance for Measuring Distribution Shift in Machine Learningcited by 2
  23. 2021A Unified Joint Maximum Mean Discrepancy for Domain Adaptationcited by 1
  24. 2022A Transfer Learning-Based Approach to Marine Vessel Re-Identificationcited by 1
  25. 2023DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systemscited by 1
  26. 2023Prototypical Cross-domain Knowledge Transfer for Cervical Dysplasia Visual Inspectioncited by 1
  27. 2024Transferable-guided Attention Is All You Need for Video Domain Adaptationcited by 1
  28. 2025M3DA: Benchmark for Unsupervised Domain Adaptation in 3D Medical Image Segmentationcited by 1
  29. 2025Feature-Weighted MMD-CORAL for Domain Adaptation in Power Transformer Fault Diagnosiscited by 1
  30. 2021Gradient Regularized Contrastive Learning for Continual Domain Adaptationcited by 0
  31. 2021Robust Ensembling Network for Unsupervised Domain Adaptationcited by 0
  32. 2021Cross-domain Trajectory Prediction with CTP-Netcited by 0
  33. 2021Domain Adaptation with Category Attention Network for Deep Sentiment Analysiscited by 0
  34. 2022Source data selection for out-of-domain generalizationcited by 0
  35. 2023A ModelOps-based Framework for Intelligent Medical Knowledge Extractioncited by 0
  36. 2023Deep Feature Registration for Unsupervised Domain Adaptationcited by 0
  37. 2025Integration of TinyML and LargeML: A Survey of 6G and Beyondcited by 0
  38. 2025The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AIcited by 0

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