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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 1251–1275 of 1854 papers

TitleStatusHype
Towards Controllable and Photorealistic Region-wise Image Manipulation—0
Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose TransferCode1
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image GenerationCode1
Vector-Decomposed Disentanglement for Domain-Invariant Object DetectionCode1
Unsupervised Disentanglement without Autoencoding: Pitfalls and Future DirectionsCode0
No-Reference Image Quality Assessment by Hallucinating Pristine FeaturesCode1
A Unified Model for Zero-shot Music Source Separation, Transcription and SynthesisCode1
Counterfactuals to Control Latent Disentangled Text Representations for Style Transfer—0
Is Disentanglement enough? On Latent Representations for Controllable Music GenerationCode1
Fair Representation Learning using Interpolation Enabled Disentanglement—0
Physics-informed Guided Disentanglement in Generative NetworksCode1
Text Classification and Clustering with Annealing Soft Nearest Neighbor Loss—0
AD-GAN: End-to-end Unsupervised Nuclei Segmentation with Aligned Disentangling TrainingCode0
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICACode1
β-Annealed Variational Autoencoder for glitches—0
Discriminator-Free Generative Adversarial AttackCode1
A Systematical Solution for Face De-identification—0
Adversarial Continual Learning for Multi-Domain Hippocampal SegmentationCode1
StyleFusion: A Generative Model for Disentangling Spatial SegmentsCode1
Retrieve in Style: Unsupervised Facial Feature Transfer and RetrievalCode1
Many-to-Many Voice Conversion based Feature Disentanglement using Variational Autoencoder—0
Semantic and Geometric Unfolding of StyleGAN Latent Space—0
Disentangle Your Dense Object DetectorCode1
Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation—0
Conditional Identity Disentanglement for Differential Face Morph Detection—0
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