mlsanityData to 14 Oct 2026

Joint Geometrical and Statistical Alignment for Visual Domain Adaptation

arXiv 1705.05498 ↗First posted 16 May 2017cs.CVcited by 43

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Abstract (arXiv)

This paper presents a novel unsupervised domain adaptation method for cross-domain visual recognition. We propose a unified framework that reduces the shift between domains both statistically and geometrically, referred to as Joint Geometrical and Statistical Alignment (JGSA). Specifically, we learn two coupled projections that project the source domain and target domain data into low dimensional subspaces where the geometrical shift and distribution shift are reduced simultaneously. The objective function can be solved efficiently in a closed form. Extensive experiments have verified that the proposed method significantly outperforms several state-of-the-art domain adaptation methods on a synthetic dataset and three different real world cross-domain visual recognition tasks.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 May 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 16; 2022: 13; 2023: 4; 2024: 3; 2025: 4; 2026: 3.

43 papers.

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  1. 2021Self-Supervised Training Enhances Online Continual Learningcited by 54
  2. 2021Learning Compatible Embeddingscited by 37
  3. 2021ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptationcited by 33
  4. 2021A Survey of Unsupervised Domain Adaptation for Visual Recognitioncited by 31
  5. 2021Aligning Correlation Information for Domain Adaptation in Action Recognitioncited by 30
  6. 2021Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Networkcited by 17
  7. 2023Partial Identifiability for Domain Adaptationcited by 14
  8. 2021Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matchingcited by 9
  9. 2022Robust Local Preserving and Global Aligning Network for Adversarial Domain Adaptationcited by 8
  10. 2022Consistency and Diversity induced Human Motion Segmentationcited by 7
  11. 2022Improving Pseudo Labels With Intra-Class Similarity for Unsupervised Domain Adaptationcited by 7
  12. 2023Effective Pseudo-Labeling based on Heatmap for Unsupervised Domain Adaptation in Cell Detectioncited by 7
31 more
  1. 2022Attention Regularized Laplace Graph for Domain Adaptationcited by 5
  2. 2021Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptationcited by 4
  3. 2022On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Modelscited by 4
  4. 20223D Shape Knowledge Graph for Cross-domain 3D Shape Retrievalcited by 4
  5. 2021Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learningcited by 3
  6. 2021A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithmscited by 3
  7. 2021Deep Least Squares Alignment for Unsupervised Domain Adaptationcited by 3
  8. 2022A Multi-stage Framework with Mean Subspace Computation and Recursive Feedback for Online Unsupervised Domain Adaptationcited by 3
  9. 2024M3D: Manifold-based Domain Adaptation with Dynamic Distribution for Non-Deep Transfer Learning in Cross-subject and Cross-session EEG-based Emotion Recognitioncited by 3
  10. 2021Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reductioncited by 2
  11. 2022Distributionally Robust Domain Adaptationcited by 2
  12. 2025Heterogeneous-Modal Unsupervised Domain Adaptation via Latent Space Bridgingcited by 2
  13. 2026OSCAR: Open-Set CAD Retrieval from a Language Prompt and a Single Imagecited by 2
  14. 2021A Unified Joint Maximum Mean Discrepancy for Domain Adaptationcited by 1
  15. 2021Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weightcited by 1
  16. 2021Cross-domain error minimization for unsupervised domain adaptationcited by 1
  17. 2022Cycle Label-Consistent Networks for Unsupervised Domain Adaptationcited by 1
  18. 2022Consecutive Knowledge Meta-Adaptation Learning for Unsupervised Medical Diagnosiscited by 1
  19. 2022On Fine-Tuned Deep Features for Unsupervised Domain Adaptationcited by 1
  20. 2025Beyond Batch Learning: Global Awareness Enhanced Domain Adaptationcited by 1
  21. 2021Grassmannian Graph-attentional Landmark Selection for Domain Adaptationcited by 0
  22. 2022On the Equity of Nuclear Norm Maximization in Unsupervised Domain Adaptationcited by 0
  23. 2022Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Predictioncited by 0
  24. 2023Constructive Incremental Learning for Fault Diagnosis of Rolling Bearings with Ensemble Domain Adaptationcited by 0
  25. 2023Deep Feature Registration for Unsupervised Domain Adaptationcited by 0
  26. 2024Learning to Discover Knowledge: A Weakly-Supervised Partial Domain Adaptation Approachcited by 0
  27. 2024CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Communitycited by 0
  28. 2025Decision Boundary Optimization-Informed Domain Adaptationcited by 0
  29. 2025Towards Conditional Feature Alignment for Cross-Domain Countingcited by 0
  30. 2026A Source-Free Approach for Domain Adaptation via Multiview Image Transformation and Latent Space Consistencycited by 0
  31. 2026Transfer learning via interpolating structurescited by 0