mlsanityData to 7 Oct 2026

Simultaneous Deep Transfer Across Domains and Tasks

arXiv 1510.02192 ↗First posted 8 Oct 2015cs.CVcited by 205

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Abstract (arXiv)

Recent reports suggest that a generic supervised deep CNN model trained on a large-scale dataset reduces, but does not remove, dataset bias. Fine-tuning deep models in a new domain can require a significant amount of labeled data, which for many applications is simply not available. We propose a new CNN architecture to exploit unlabeled and sparsely labeled target domain data. Our approach simultaneously optimizes for domain invariance to facilitate domain transfer and uses a soft label distribution matching loss to transfer information between tasks. Our proposed adaptation method offers empirical performance which exceeds previously published results on two standard benchmark visual domain adaptation tasks, evaluated across supervised and semi-supervised adaptation settings.

Key facts. Cited by 205 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Oct 2015.

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Citing papers per year: 2021: 75; 2022: 53; 2023: 32; 2024: 27; 2025: 14; 2026: 4.

205 papers.

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  1. 2023Robust Test-Time Adaptation in Dynamic Scenarioscited by 185
  2. 2022Causal Transformer for Estimating Counterfactual Outcomescited by 121
  3. 2021Deep Subdomain Adaptation Network for Image Classificationcited by 119
  4. 2021AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptationcited by 104
  5. 2022Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectivescited by 98
  6. 2021Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learningcited by 78
  7. 2022Semantic-Aware Domain Generalized Segmentationcited by 78
  8. 2022Test-Time Adaptation via Self-Training with Nearest Neighbor Informationcited by 64
  9. 2023Domain Adaptation for Time Series Under Feature and Label Shiftscited by 60
  10. 2022FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosiscited by 59
  11. 2022Transferability in Deep Learning: A Surveycited by 57
  12. 2021Incorporating Domain Knowledge into Deep Neural Networkscited by 56
38 more
  1. 2021Active Learning for Domain Adaptation: An Energy-Based Approachcited by 53
  2. 2021Intra-Inter Camera Similarity for Unsupervised Person Re-Identificationcited by 52
  3. 2021Understanding and Mitigating Annotation Bias in Facial Expression Recognitioncited by 50
  4. 2021Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Datacited by 48
  5. 2022Discover and Mitigate Unknown Biases with Debiasing Alternate Networkscited by 47
  6. 2021Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentationcited by 46
  7. 2021Source-Free Domain Adaptation for Image Segmentationcited by 45
  8. 2021Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detectioncited by 45
  9. 2021Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Densitycited by 44
  10. 2021Semi-Supervised Domain Generalization with Stochastic StyleMatchcited by 43
  11. 2021Your Classifier can Secretly Suffice Multi-Source Domain Adaptationcited by 42
  12. 2022Aligning Domain-specific Distribution and Classifier for Cross-domain Classification from Multiple Sourcescited by 42
  13. 2021Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentationcited by 39
  14. 2021DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptationcited by 37
  15. 2022Using Language to Extend to Unseen Domainscited by 34
  16. 2025Model Adaptation: Unsupervised Domain Adaptation without Source Datacited by 34
  17. 2021ECACL: A Holistic Framework for Semi-Supervised Domain Adaptationcited by 31
  18. 2021A Survey of Unsupervised Domain Adaptation for Visual Recognitioncited by 31
  19. 2022Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignmentcited by 31
  20. 2021Aligning Correlation Information for Domain Adaptation in Action Recognitioncited by 30
  21. 2022Bias Mimicking: A Simple Sampling Approach for Bias Mitigationcited by 30
  22. 2022Understanding Why Generalized Reweighting Does Not Improve Over ERMcited by 29
  23. 2023Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalizationcited by 29
  24. 2022GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalizationcited by 28
  25. 2021Domain-Specific Suppression for Adaptive Object Detectioncited by 26
  26. 2023Semantic Image Segmentation: Two Decades of Researchcited by 26
  27. 2021Leveraging Self-Supervision for Cross-Domain Crowd Countingcited by 24
  28. 2021Unsupervised Domain Adaptation: A Reality Checkcited by 24
  29. 2022Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classificationcited by 23
  30. 2022Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Trainingcited by 22
  31. 2022Multimodal Across Domains Gaze Target Detectioncited by 22
  32. 2023A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directionscited by 22
  33. 2024Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approachcited by 22
  34. 2022CAFA: Class-Aware Feature Alignment for Test-Time Adaptationcited by 21
  35. 2021AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detectioncited by 19
  36. 2021Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Surveycited by 19
  37. 2022Multi-Representation Adaptation Network for Cross-domain Image Classificationcited by 19
  38. 2022Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictorscited by 19

50 most cited of 205 All 205 (JSON)