GAPan uses invertible normalizing flows to learn generative appearance priors from seen categories and aligns retrieval embeddings to these priors, improving performance on unseen categories in fine-grained image retrieval.
Why normalizing flows fail to detect out-of- distribution data.Advances in neural information processing systems, 33:20578–20589
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Learning to Align Generative Appearance Priors for Fine-grained Image Retrieval
GAPan uses invertible normalizing flows to learn generative appearance priors from seen categories and aligns retrieval embeddings to these priors, improving performance on unseen categories in fine-grained image retrieval.