4 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
Text-to-Image Models Need Less from Text Encoders Than You Think
Nurit Spingarn, Noa Cohen, Tamar Rott Shaham +1
Text-to-image models rely on text prompts as their primary interface to human intent. Prompts are encoded by a text encoder into embeddings that condition the image generation proc…
MineTheGap: Automatic Mining of Biases in Text-to-Image Models
Noa Cohen, Nurit Spingarn-Eliezer, Inbar Huberman-Spiegelglas +1
Text-to-Image (TTI) models generate images based on text prompts, which often leave certain aspects of the desired image ambiguous. When faced with these ambiguities, TTI models ha…
From Posterior Sampling to Meaningful Diversity in Image Restoration
Noa Cohen, Hila Manor, Yuval Bahat +1
Image restoration problems are typically ill-posed in the sense that each degraded image can be restored in infinitely many valid ways. To accommodate this, many works generate a d…