Diffusion models are the main driver of progress in image and video synthesis, but suffer
from slow inference speed. Distillation methods, like the recently introduced adversarial …

This paper for the first time explores text-to-image diffusion models for Zero-Shot Sketch-
based Image Retrieval (ZS-SBIR). We highlight a pivotal discovery: the capacity of text-to …

Biological and artificial information processing systems form representations of the world
that they can use to categorize, reason, plan, navigate, and make decisions. To what extent …

We address the problem of synthesizing multi-view optical illusions: images that change
appearance upon a transformation such as a flip or rotation. We propose a simple zero-shot …

Following the recent popularity of Large Language Models (LLMs), several attempts have
been made to extend them to the visual domain. From having a visual assistant that could …

With recent advances in image and video diffusion models for content creation a plethora of
techniques have been proposed for customizing their generated content. In particular …

The robust generalization of models to rare in-distribution (ID) samples drawn from the long
tail of the training distribution and to out-of-training-distribution (OOD) samples is one of the …

Given a factorization of an image into a sum of linear components, we present a zero-shot
method to control each individual component through diffusion model sampling. For …

Biomedical imaging datasets are often small and biased, meaning that real-world
performance of predictive models can be substantially lower than expected from internal …

Human ability to recognize complex visual patterns arises through transformations
performed by successive areas in the ventral visual cortex. Deep neural networks trained …