Disentangled Contrastive Learning From Synthetic Matching Pairs for Targeted Chest X-Ray Generation

Disentangled generation enables the synthesis of images with explicit control over disentangled attributes. However, traditional generative models often struggle to independently disentangle these attributes while maintaining the ability to generate entirely new, fully randomized, and diverse synthe...

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Bibliographic Details
Main Authors: Euyoung Kim, Soochahn Lee, Kyoung Mu Lee
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10844299/
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