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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 26–50 of 1854 papers

TitleStatusHype
When StyleGAN Meets Stable Diffusion: a W+ Adapter for Personalized Image GenerationCode2
StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style AdapterCode2
BlendFace: Re-designing Identity Encoders for Face-SwappingCode2
EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face AnimationCode2
A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild ImagesCode2
DPE: Disentanglement of Pose and Expression for General Video Portrait EditingCode2
Generative Time Series Forecasting with Diffusion, Denoise, and DisentanglementCode2
eVAE: Evolutionary Variational AutoencoderCode2
Fine-Grained Face Swapping via Regional GAN InversionCode2
Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical PerspectivesCode2
3DFaceShop: Explicitly Controllable 3D-Aware Portrait GenerationCode2
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling SpeakersCode2
MotionCLIP: Exposing Human Motion Generation to CLIP SpaceCode2
Third Time's the Charm? Image and Video Editing with StyleGAN3Code2
Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty LearningCode2
Compositional Transformers for Scene GenerationCode2
Compositional Transformers for Scene GenerationCode2
Generative Adversarial TransformersCode2
Learning an Animatable Detailed 3D Face Model from In-The-Wild ImagesCode2
Stylized Neural PaintingCode2
CausalVAE: Structured Causal Disentanglement in Variational AutoencoderCode2
Adversarial Latent AutoencodersCode2
Interpreting the Latent Space of GANs for Semantic Face EditingCode2
Challenging Common Assumptions in the Unsupervised Learning of Disentangled RepresentationsCode2
A Style-Based Generator Architecture for Generative Adversarial NetworksCode2
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