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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 21–30 of 1854 papers

TitleStatusHype
Challenging Common Assumptions in the Unsupervised Learning of Disentangled RepresentationsCode2
ColorPeel: Color Prompt Learning with Diffusion Models via Color and Shape DisentanglementCode2
DPE: Disentanglement of Pose and Expression for General Video Portrait EditingCode2
Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty LearningCode2
Apply Hierarchical-Chain-of-Generation to Complex Attributes Text-to-3D GenerationCode2
EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face AnimationCode2
A Style-Based Generator Architecture for Generative Adversarial NetworksCode2
DiffArtist: Towards Structure and Appearance Controllable Image StylizationCode2
Fine-Grained Face Swapping via Regional GAN InversionCode2
BlendFace: Re-designing Identity Encoders for Face-SwappingCode2
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