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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 1651–1660 of 1854 papers

TitleStatusHype
Identity-Disentangled Neural Deformation Model for Dynamic Meshes—0
IdentityDP: Differential Private Identification Protection for Face Images—0
Identity From Here, Pose From There: Self-Supervised Disentanglement and Generation of Objects Using Unlabeled Videos—0
IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction—0
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre—0
iFADIT: Invertible Face Anonymization via Disentangled Identity Transform—0
IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime Talking Head Generation—0
Illumination-Adaptive Person Re-identification—0
Image Denoising via Style Disentanglement—0
Image Disentanglement and Uncooperative Re-Entanglement for High-Fidelity Image-to-Image Translation—0
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