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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 561–570 of 1854 papers

TitleStatusHype
GenDeF: Learning Generative Deformation Field for Video Generation—0
Bottom-Up Instance Segmentation of Catheters for Chest X-Rays—0
Language-Informed Visual Concept LearningCode1
AttriHuman-3D: Editable 3D Human Avatar Generation with Attribute Decomposition and Indexing—0
Dancing with Still Images: Video Distillation via Static-Dynamic DisentanglementCode1
Text Attribute Control via Closed-Loop Disentanglement—0
StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style AdapterCode2
Clustering Inductive Biases with Unrolled Networks—0
DEVIAS: Learning Disentangled Video Representations of Action and SceneCode1
Benchmarking and Enhancing Disentanglement in Concept-Residual Models—0
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