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Found 2 papers, 1 papers with code
SALAD: Source-free Active Label-Agnostic Domain Adaptation for Classification, Segmentation and Detection
SALAD has three key benefits: (i) it is task-agnostic, and can be applied across various visual tasks such as classification, segmentation and detection; (ii) it can handle shifts in output label space from the pre-trained source network to the target domain; (iii) it does not require access to source data for adaptation.
Learning Colour Representations of Search Queries
We leverage historical clickthrough data to produce a colour representation for search queries and propose a recurrent neural network architecture to encode unseen queries into colour space.
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