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Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation

arXiv 1803.11365 ↗First posted 30 Mar 2018cs.CVcited by 218

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Abstract (arXiv)

Can we detect common objects in a variety of image domains without instance-level annotations? In this paper, we present a framework for a novel task, cross-domain weakly supervised object detection, which addresses this question. For this paper, we have access to images with instance-level annotations in a source domain (e.g., natural image) and images with image-level annotations in a target domain (e.g., watercolor). In addition, the classes to be detected in the target domain are all or a subset of those in the source domain. Starting from a fully supervised object detector, which is pre-trained on the source domain, we propose a two-step progressive domain adaptation technique by fine-tuning the detector on two types of artificially and automatically generated samples. We test our methods on our newly collected datasets containing three image domains, and achieve an improvement of approximately 5 to 20 percentage points in terms of mean average precision (mAP) compared to the best-performing baselines.

Key facts. Cited by 218 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Mar 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 40; 2022: 36; 2023: 44; 2024: 42; 2025: 34; 2026: 22.

218 papers.

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  1. 2023Cut and Learn for Unsupervised Object Detection and Instance Segmentationcited by 186
  2. 2021Cross-Domain Adaptive Teacher for Object Detectioncited by 125
  3. 2022Exploiting Unlabeled Data with Vision and Language Models for Object Detectioncited by 97
  4. 2021Unsupervised Domain Adaptation of Object Detectors: A Surveycited by 93
  5. 2022High-Quality Entity Segmentationcited by 93
  6. 2023CLIP the Gap: A Single Domain Generalization Approach for Object Detectioncited by 87
  7. 2021Class-agnostic Object Detection with Multi-modal Transformercited by 85
  8. 2022Self-Training: A Surveycited by 85
  9. 2022A Closer Look at Smoothness in Domain Adversarial Trainingcited by 85
  10. 2021Weakly Supervised Object Localization and Detection: A Surveycited by 84
  11. 2022SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detectioncited by 74
  12. 2023Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenescited by 68
38 more
  1. 2021Uncertainty-Aware Unsupervised Domain Adaptation in Object Detectioncited by 59
  2. 2022Instance Relation Graph Guided Source-Free Domain Adaptive Object Detectioncited by 55
  3. 2021MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptationcited by 54
  4. 2023Contrastive Mean Teacher for Domain Adaptive Object Detectorscited by 52
  5. 2021Vector-Decomposed Disentanglement for Domain-Invariant Object Detectioncited by 47
  6. 2024Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detectorcited by 43
  7. 2023Text-image Alignment for Diffusion-based Perceptioncited by 42
  8. 2021Spectral Unsupervised Domain Adaptation for Visual Recognitioncited by 40
  9. 2021Decoupled Adaptation for Cross-Domain Object Detectioncited by 37
  10. 2022Task-specific Inconsistency Alignment for Domain Adaptive Object Detectioncited by 37
  11. 2021Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularizationcited by 36
  12. 2022Towards Online Domain Adaptive Object Detectioncited by 36
  13. 2023COCO-O: A Benchmark for Object Detectors under Natural Distribution Shiftscited by 34
  14. 2022Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptationcited by 33
  15. 2024AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Modelscited by 29
  16. 2024Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignmentcited by 29
  17. 2021HLA-Face: Joint High-Low Adaptation for Low Light Face Detectioncited by 28
  18. 2022InstaFormer: Instance-Aware Image-to-Image Translation with Transformercited by 28
  19. 2022Multi-Granularity Alignment Domain Adaptation for Object Detectioncited by 28
  20. 2021I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectorscited by 27
  21. 2021GAIA: A Transfer Learning System of Object Detection that Fits Your Needscited by 27
  22. 2021SimROD: A Simple Adaptation Method for Robust Object Detectioncited by 27
  23. 2021Domain-Specific Suppression for Adaptive Object Detectioncited by 26
  24. 2022Gradual Domain Adaptation without Indexed Intermediate Domainscited by 26
  25. 2022Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embeddingcited by 25
  26. 2023Adversarial Alignment for Source Free Object Detectioncited by 25
  27. 2021DA-DETR: Domain Adaptive Detection Transformer with Information Fusioncited by 24
  28. 2021Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detectioncited by 24
  29. 2025Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detectioncited by 24
  30. 2023DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detectioncited by 23
  31. 2023DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasetscited by 23
  32. 2021Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detectioncited by 21
  33. 2021Memory-guided Unsupervised Image-to-image Translationcited by 21
  34. 2023Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detectioncited by 21
  35. 2022Towards Robust Adaptive Object Detection under Noisy Annotationscited by 20
  36. 2024The Manga Whisperer: Automatically Generating Transcriptions for Comicscited by 20
  37. 2021AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detectioncited by 19
  38. 2022SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detectioncited by 19

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