mlsanityData to 7 Oct 2026

Learning Attributes Equals Multi-Source Domain Generalization

arXiv 1605.00743 ↗First posted 3 May 2016cs.CVcited by 44

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Abstract (arXiv)

Attributes possess appealing properties and benefit many computer vision problems, such as object recognition, learning with humans in the loop, and image retrieval. Whereas the existing work mainly pursues utilizing attributes for various computer vision problems, we contend that the most basic problem---how to accurately and robustly detect attributes from images---has been left under explored. Especially, the existing work rarely explicitly tackles the need that attribute detectors should generalize well across different categories, including those previously unseen. Noting that this is analogous to the objective of multi-source domain generalization, if we treat each category as a domain, we provide a novel perspective to attribute detection and propose to gear the techniques in multi-source domain generalization for the purpose of learning cross-category generalizable attribute detectors. We validate our understanding and approach with extensive experiments on four challenging datasets and three different problems.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 May 2016.

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Citing papers per year: 2021: 24; 2022: 9; 2023: 5; 2024: 3; 2025: 2; 2026: 1.

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  1. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 762
  2. 2021Domain Generalization: A Surveycited by 760
  3. 2021Towards Out-Of-Distribution Generalization: A Surveycited by 431
  4. 2021Domain Adaptation for Medical Image Analysis: A Surveycited by 351
  5. 2021Prompting Visual-Language Models for Efficient Video Understandingcited by 309
  6. 2021FSDR: Frequency Space Domain Randomization for Domain Generalizationcited by 163
  7. 2021Model-Based Domain Generalizationcited by 103
  8. 2022NICO++: Towards Better Benchmarking for Domain Generalizationcited by 86
  9. 2022Semantic-Aware Domain Generalized Segmentationcited by 78
  10. 2021Elaborative Rehearsal for Zero-shot Action Recognitioncited by 76
  11. 2021Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentationcited by 56
  12. 2023Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignmentcited by 47
32 more
  1. 2021Contrastive Syn-to-Real Generalizationcited by 32
  2. 2021WEDGE: Web-Image Assisted Domain Generalization for Semantic Segmentationcited by 25
  3. 2021Relation-aware Compositional Zero-shot Learning for Attribute-Object Pair Recognitioncited by 19
  4. 2021MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identificationcited by 18
  5. 2021Object Priors for Classifying and Localizing Unseen Actionscited by 15
  6. 2023Synthetic Sample Selection for Generalized Zero-Shot Learningcited by 14
  7. 2021CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognitioncited by 12
  8. 2022Alignment-Uniformity aware Representation Learning for Zero-shot Video Classificationcited by 11
  9. 2021Transferring Knowledge from Text to Video: Zero-Shot Anticipation for Procedural Actionscited by 10
  10. 2022A diverse large-scale building dataset and a novel plug-and-play domain generalization method for building extractioncited by 10
  11. 2023Complementary Domain Adaptation and Generalization for Unsupervised Continual Domain Shift Learningcited by 9
  12. 2021Learning Single/Multi-Attribute of Object with Symmetry and Groupcited by 8
  13. 2021Zero-Shot Action Recognition from Diverse Object-Scene Compositionscited by 8
  14. 2022HMOE: Hypernetwork-based Mixture of Experts for Domain Generalizationcited by 8
  15. 2024ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognitioncited by 8
  16. 2023Best-Effort Adaptationcited by 7
  17. 2021Self-balanced Learning For Domain Generalizationcited by 5
  18. 2021Improving Deep Metric Learning by Divide and Conquercited by 5
  19. 2021ZS-SLR: Zero-Shot Sign Language Recognition from RGB-D Videoscited by 4
  20. 2022Universal Prototype Transport for Zero-Shot Action Recognition and Localizationcited by 4
  21. 2023Telling Stories for Common Sense Zero-Shot Action Recognitioncited by 4
  22. 2021Multi-Modal Zero-Shot Sign Language Recognitioncited by 3
  23. 2022An Iterative Co-Training Transductive Framework for Zero Shot Learningcited by 3
  24. 2021GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognitioncited by 2
  25. 2025Why Domain Generalization Fail? A View of Necessity and Sufficiencycited by 2
  26. 2022End-to-End Semantic Video Transformer for Zero-Shot Action Recognitioncited by 1
  27. 2024Semantic-Rearrangement-Based Multi-Level Alignment for Domain Generalized Segmentationcited by 1
  28. 2026Bipartite Mode Matching for Vision Training Set Search from a Hierarchical Data Servercited by 1
  29. 2021Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNetcited by 0
  30. 2022Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learningcited by 0
  31. 2024Overcoming Data Inequality across Domains with Semi-Supervised Domain Generalizationcited by 0
  32. 2025Multi-Granularity Feature Calibration via VFM for Domain Generalized Semantic Segmentationcited by 0