xrenaa/Retriever
[ICLR2022] Code for "Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph"
This project helps researchers and developers explore the core components of various media, like speech or images, by separating 'what it is' from 'how it looks or sounds.' It takes input data (e.g., an audio clip, an image) and outputs disentangled content and style representations. Scientists and engineers working on advanced media manipulation or generation tasks would use this.
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Use this if you need to perform unsupervised disentanglement of content and style from various media types, for applications like zero-shot voice conversion, co-part segmentation, or style transfer.
Not ideal if you're looking for a ready-to-use application for end-users, as this provides research code for underlying representation learning.
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Oct 19, 2022
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