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Disentanglement

This is an approach to solve a diverse set of tasks in a data efficient manner by disentangling (or isolating ) the underlying structure of the main problem into disjoint parts of its representations. This disentanglement can be done by focussing on the "transformation" properties of the world(main problem)

Papers

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Showing 1351–1360 of 1854 papers

TitleStatusHype
Neural Video Portrait Relighting in Real-time via Consistency ModelingCode1
Unsupervised Disentanglement of Linear-Encoded Facial Semantics—0
PointBA: Towards Backdoor Attacks in 3D Point Cloud—0
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and TranslationCode1
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval—0
Disentanglement-based Cross-Domain Feature Augmentation for Effective Unsupervised Domain Adaptive Person Re-identification—0
Scaling-up Disentanglement for Image TranslationCode1
Closing the Loop: Joint Rain Generation and Removal via Disentangled Image Translation—0
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges—0
GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images—0
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