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Yuval Alaluf

7 accepted papers

2025

NeuralSVG: An Implicit Representation for Text-to-Vector Generation

ICCV 2025poster

Vector graphics are essential in design, providing artists with a versatile medium for creating resolution-independent and highly editable visual content. Recent advancements in vision-language and diffusion models have fueled interest in text-to-vector graphics generation. However, existing approac…

2024

Breathing Life Into Sketches Using Text-to-Video Priors

CVPR 2024highlight

A sketch is one of the most intuitive and versatile tools humans use to convey their ideas visually. An animated sketch opens another dimension to the expression of ideas and is widely used by designers for a variety of purposes. Animating sketches is a laborious process requiring extensive experien…

Cited by 29SourcePDFScholar
2023

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

ICLR 2023top-25%

Text-to-image models offer unprecedented freedom to guide creation through natural language. Yet, it is unclear how such freedom can be exercised to generate images of specific unique concepts, modify their appearance, or compose them in new roles and novel scenes. In other words, we ask: how can we…

2023

CLIPascene: Scene Sketching with Different Types and Levels of Abstraction

ICCV 2023oral

In this paper, we present a method for converting a given scene image into a sketch using different types and multiple levels of abstraction. We distinguish between two types of abstraction. The first considers the fidelity of the sketch, varying its representation from a more precise portrayal of…

Cited by 101PDFScholar
2022

HyperStyle: StyleGAN Inversion With HyperNetworks for Real Image Editing

CVPR 2022poster

The inversion of real images into StyleGAN's latent space is a well-studied problem. Nevertheless, applying existing approaches to real-world scenarios remains an open challenge, due to an inherent trade-off between reconstruction and editability: latent space regions which can accurately represent…

Cited by 330PDFcodeScholar
2021

Encoding in Style: A StyleGAN Encoder for Image-to-Image Translation

CVPR 2021poster

We present a generic image-to-image translation framework, pixel2style2pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style vectors which are fed into a pretrained StyleGAN generator, forming the extended W+ latent space. We first show that our…

Cited by 1395PDFcodeScholar