Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
Deep unsupervised learning using nonequilibrium thermodynamics
3 Pith papers cite this work. Polarity classification is still indexing.
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PNG model learns high-dimensional prompt features to generate realistic noisy sRGB images consistent with input noise distribution without camera metadata.
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Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization
Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
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Diffusion-Based sRGB Real Noise Generation via Prompt-Driven Noise Representation Learning
PNG model learns high-dimensional prompt features to generate realistic noisy sRGB images consistent with input noise distribution without camera metadata.
- Optimization-Guided Diffusion for Interactive Scene Generation