AI RESEARCH
FACTOR: Counterfactual Training-Free Test-Time Adaptation for Open-Vocabulary Object Detection
arXiv CS.CV
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ArXi:2605.03294v1 Announce Type: new Open-vocabulary object detection often fails under distribution shifts, as it can be misled by spurious correlations between non-causal visual attributes (e.g., brightness, texture) and object categories. Existing test-time adaptation (TTA) methods either depend on costly online optimization or perform global calibration, overlooking the attribute-specific nature of these failures. To address this, we propose FACTOR (counterFACtual