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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 91–100 of 1854 papers

TitleStatusHype
DIFFER: Disentangling Identity Features via Semantic Cues for Clothes-Changing Person Re-IDCode1
CMD-HAR: Cross-Modal Disentanglement for Wearable Human Activity Recognition—0
NeuroLIP: Interpretable and Fair Cross-Modal Alignment of fMRI and Phenotypic Text—0
Exploring Disentangled and Controllable Human Image Synthesis: From End-to-End to Stage-by-Stage—0
SLIP: Spoof-Aware One-Class Face Anti-Spoofing with Language Image PretrainingCode0
DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model—0
Fast and Physically-based Neural Explicit Surface for Relightable Human Avatars—0
Seeing Speech and Sound: Distinguishing and Locating Audios in Visual Scenes—0
Re-HOLD: Video Hand Object Interaction Reenactment via adaptive Layout-instructed Diffusion Model—0
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation—0
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