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Source-Free Object Detection With Detection Transformer.

Huizai Yao, Sicheng Zhao, Shuo Lu

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |September 16, 2025
    PubMed
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    This study introduces FRANCK, a novel framework for Source-Free Object Detection (SFOD) tailored for Detection Transformers (DETR). FRANCK enhances knowledge transfer to unsupervised domains, achieving state-of-the-art results.

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Artificial Intelligence

    Background:

    • Source-Free Object Detection (SFOD) facilitates knowledge transfer to unsupervised domains without source data.
    • Existing SFOD methods often lack tailored adaptations for advanced architectures like Detection Transformers (DETR).

    Purpose of the Study:

    • To introduce FRANCK, a novel SFOD framework specifically designed for query-centric feature enhancement in DETR models.
    • To improve the robustness and generalization of object detection models in unsupervised target domains.

    Main Methods:

    • FRANCK integrates four key components: Objectness Score-based Sample Reweighting (OSSR), Contrastive Learning with Matching-based Memory Bank (CMMB), Uncertainty-weighted Query-fused Feature Distillation (UQFD), and a Dynamic Teacher Updating Interval (DTUI) self-training pipeline.

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  • OSSR reweights detection loss using attention-based objectness scores.
  • CMMB enhances class-wise contrastive learning via multi-level feature memory banks.
  • UQFD improves feature distillation through query feature fusion and prediction quality reweighting.

    • Main Results:

    • FRANCK effectively adapts source-pre-trained DETR models to target domains.
    • The proposed method demonstrates enhanced robustness and generalization capabilities.
    • Experiments on multiple benchmarks show state-of-the-art performance, validating FRANCK's effectiveness.

    Conclusions:

    • FRANCK offers a specialized and effective solution for Source-Free Object Detection within the DETR architecture.
    • The framework significantly advances the capabilities of unsupervised domain adaptation for object detection.
    • FRANCK's components collectively contribute to superior performance and compatibility with DETR-based SFOD models.