472 citations · 538 across the 20 of their papers we have counts for
23 papers
VideoSketcher: Sequential Sketch Generation Using Video Model Priors
Hui Ren, Yuval Alaluf, Omer Bar Tal +3
Sketching is inherently sequential: strokes are drawn progressively to explore and refine ideas. Yet most generative approaches treat sketches as static images, ignoring the tempor…
Piece it Together: Part-Based Concepting with IP-Priors
Elad Richardson, Kfir Goldberg, Yuval Alaluf +1
Advanced generative models excel at synthesizing images but often rely on text-based conditioning. Visual designers, however, often work beyond language, directly drawing inspirati…
NeuralSVG: An Implicit Representation for Text-to-Vector Generation
Sagi Polaczek, Yuval Alaluf, Elad Richardson +2
Vector graphics are essential in design, providing artists with a versatile medium for creating resolution-independent and highly editable visual content. Recent advancements in vi…
InstantRestore: Single-Step Personalized Face Restoration with Shared-Image Attention
Howard Zhang, Yuval Alaluf, Sizhuo Ma +3
Face image restoration aims to enhance degraded facial images while addressing challenges such as diverse degradation types, real-time processing demands, and, most crucially, the…
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation
Rinon Gal, Adi Haviv, Yuval Alaluf +3
The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components. While workflow-based app…
pOps: Photo-Inspired Diffusion Operators
Elad Richardson, Yuval Alaluf, Ali Mahdavi-Amiri +1
Text-guided image generation enables the creation of visual content from textual descriptions. However, certain visual concepts cannot be effectively conveyed through language alon…
MyVLM: Personalizing VLMs for User-Specific Queries
Yuval Alaluf, Elad Richardson, Sergey Tulyakov +2
Recent large-scale vision-language models (VLMs) have demonstrated remarkable capabilities in understanding and generating textual descriptions for visual content. However, these m…
Breathing Life Into Sketches Using Text-to-Video Priors
Rinon Gal, Yael Vinker, Yuval Alaluf +4
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 wi…
Cross-Image Attention for Zero-Shot Appearance Transfer
Yuval Alaluf, Daniel Garibi, Or Patashnik +2
Recent advancements in text-to-image generative models have demonstrated a remarkable ability to capture a deep semantic understanding of images. In this work, we leverage this sem…
ConceptLab: Creative Concept Generation using VLM-Guided Diffusion Prior Constraints
Elad Richardson, Kfir Goldberg, Yuval Alaluf +1
Recent text-to-image generative models have enabled us to transform our words into vibrant, captivating imagery. The surge of personalization techniques that has followed has also…
A Neural Space-Time Representation for Text-to-Image Personalization
Yuval Alaluf, Elad Richardson, Gal Metzer +1
A key aspect of text-to-image personalization methods is the manner in which the target concept is represented within the generative process. This choice greatly affects the visual…
TEXTure: Text-Guided Texturing of 3D Shapes
Elad Richardson, Gal Metzer, Yuval Alaluf +2
In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion mode…
Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models
Hila Chefer, Yuval Alaluf, Yael Vinker +2
Recent text-to-image generative models have demonstrated an unparalleled ability to generate diverse and creative imagery guided by a target text prompt. While revolutionary, curre…
CLIPascene: Scene Sketching with Different Types and Levels of Abstraction
Yael Vinker, Yuval Alaluf, Daniel Cohen-Or +1
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 ab…
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon +4
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 uni…
State-of-the-Art in the Architecture, Methods and Applications of StyleGAN
Amit H. Bermano, Rinon Gal, Yuval Alaluf +5
Generative Adversarial Networks (GANs) have established themselves as a prevalent approach to image synthesis. Of these, StyleGAN offers a fascinating case study, owing to its rema…
Third Time's the Charm? Image and Video Editing with StyleGAN3
Yuval Alaluf, Or Patashnik, Zongze Wu +4
StyleGAN is arguably one of the most intriguing and well-studied generative models, demonstrating impressive performance in image generation, inversion, and manipulation. In this w…
HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing
Yuval Alaluf, Omer Tov, Ron Mokady +2
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, d…
StyleFusion: A Generative Model for Disentangling Spatial Segments
Omer Kafri, Or Patashnik, Yuval Alaluf +1
We present StyleFusion, a new mapping architecture for StyleGAN, which takes as input a number of latent codes and fuses them into a single style code. Inserting the resulting styl…
ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement
Yuval Alaluf, Or Patashnik, Daniel Cohen-Or
Recently, the power of unconditional image synthesis has significantly advanced through the use of Generative Adversarial Networks (GANs). The task of inverting an image into its c…
Designing an Encoder for StyleGAN Image Manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan +2
Recently, there has been a surge of diverse methods for performing image editing by employing pre-trained unconditional generators. Applying these methods on real images, however,…
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model
Yuval Alaluf, Or Patashnik, Daniel Cohen-Or
The task of age transformation illustrates the change of an individual's appearance over time. Accurately modeling this complex transformation over an input facial image is extreme…
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
Elad Richardson, Yuval Alaluf, Or Patashnik +4
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…