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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 1071–1080 of 1854 papers

TitleStatusHype
OPT: One-shot Pose-Controllable Talking Head Generation—0
One-Shot Face Video Re-enactment using Hybrid Latent Spaces of StyleGAN2—0
QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired DataCode0
Disentangling Learning Representations with Density EstimationCode0
Dual-interest Factorization-heads Attention for Sequential RecommendationCode0
Shortcut Detection with Variational AutoencodersCode0
Structure and Content-Guided Video Synthesis with Diffusion Models—0
PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose RestorationCode0
Divide and Compose with Score Based Generative ModelsCode0
Aggregation of Disentanglement: Reconsidering Domain Variations in Domain Generalization—0
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