Train object detector on image data without box annotation with Detic
Train object detector on image data without box annotation with Detic
Detecting Twenty-thousand Classes using Image-level Supervision
arXiv paper abstract https://arxiv.org/abs/2201.02605
arXiv PDF paper https://arxiv.org/pdf/2201.02605.pdf
Current object detectors are limited in vocabulary size due to the small scale of detection datasets.
Image classifiers, on the other hand, reason about much larger vocabularies, as their datasets are larger and easier to collect.
... propose Detic, which simply trains the classifiers of a detector on image classification data and thus expands the vocabulary of detectors to tens of thousands of concepts.
... Detic yields excellent detectors even for classes without box annotations.
It outperforms prior work on both open-vocabulary and long-tail detection benchmarks.
... train a detector with all the twenty-one-thousand classes of the ImageNet dataset and show that it generalizes to new datasets without fine-tuning. ...
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