A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning
Prevalent techniques in zero-shot learning do not generalize well to other related problem scenarios. Here, we present a unified approach for conventional zero-shot, generalized zero-shot and few-shot learning problems. Our approach is based on a novel Class Adapting Principal Directions (CAPD) concept that allows multiple embeddings of image features into a semantic space. Given an image, our method produces one principal direction for each seen class. Then, it learns how to combine these...[Show more]
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Image Processing|
|01_Rahman_A_Unified_approach_for_2018.pdf||2.65 MB||Adobe PDF||Request a copy|
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