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Synthetic Priors for Real-World Detection: a Label-Free Framework for Identifying Ultra-Rare Objects
Abstract: Detecting ultra-rare objects (frequency 10-6) without positive annotations remains a critical challenge in computer vision. We propose a Synthesis-Prior Driven paradigm that eliminates the ...
Abstract: Source-free domain adaptive object detection (SFOD) aims to transfer models pre-trained on the source domain to the unlabeled target domain without requiring access to the source data. Most ...
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