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Source Free Object Detection

Source-Free Object Detection (SFOD) is a domain adaptation challenge in which only the pretrained source model weights are available during adaptation, with no access to the source data. The model must adapt solely using unlabeled samples from the target domain

Papers

Showing 1117 of 17 papers

TitleStatusHype
Instance Relation Graph Guided Source-Free Domain Adaptive Object DetectionCode1
Source-Free Object Detection by Learning To Overlook Domain StyleCode1
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source DataCode1
Exploring Sequence Feature Alignment for Domain Adaptive Detection TransformersCode1
A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data0
Unbiased Mean Teacher for Cross-domain Object DetectionCode1
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning resultsCode1
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