10 citations · 38 across the 18 of their papers we have counts for
21 papers
Solaris: Towards Interfaces That Are Generated, Not Coded
Yuval Alaluf, Omri Avrahami, Guy Bukchin Leshem +18
Digital interfaces are traditionally implemented through intermediate representations such as code, requiring their appearance and behavior to be specified in advance. We introduce…
Inspiration Seeds: Learning Non-Literal Visual Combinations for Generative Exploration
Kfir Goldberg, Elad Richardson, Yael Vinker
While generative models have become powerful tools for image synthesis, they are typically optimized for executing carefully crafted textual prompts, offering limited support for t…
ShapeUP: Scalable Image-Conditioned 3D Editing
Inbar Gat, Dana Cohen-Bar, Guy Levy +2
Recent advancements in 3D foundation models have enabled the generation of high-fidelity assets, yet precise 3D manipulation remains a significant challenge. Existing 3D editing fr…
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…
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…
LCM-Lookahead for Encoder-based Text-to-Image Personalization
Rinon Gal, Or Lichter, Elad Richardson +4
Recent advancements in diffusion models have introduced fast sampling methods that can effectively produce high-quality images in just one or a few denoising steps. Interestingly,…
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…
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…
Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes
Dana Cohen-Bar, Elad Richardson, Gal Metzer +2
Recent breakthroughs in text-guided image generation have led to remarkable progress in the field of 3D synthesis from text. By optimizing neural radiance fields (NeRF) directly fr…
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…
NeRN -- Learning Neural Representations for Neural Networks
Maor Ashkenazi, Zohar Rimon, Ron Vainshtein +4
Neural Representations have recently been shown to effectively reconstruct a wide range of signals from 3D meshes and shapes to images and videos. We show that, when adapted correc…
Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures
Gal Metzer, Elad Richardson, Or Patashnik +2
Text-guided image generation has progressed rapidly in recent years, inspiring major breakthroughs in text-guided shape generation. Recently, it has been shown that using score dis…
Rethinking FUN: Frequency-Domain Utilization Networks
Kfir Goldberg, Stav Shapiro, Elad Richardson +1
The search for efficient neural network architectures has gained much focus in recent years, where modern architectures focus not only on accuracy but also on inference time and mo…
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…
It's All About The Scale -- Efficient Text Detection Using Adaptive Scaling
Elad Richardson, Yaniv Azar, Or Avioz +4
"Text can appear anywhere". This property requires us to carefully process all the pixels in an image in order to accurately localize all text instances. In particular, for the mor…
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
Matan Sela, Elad Richardson, Ron Kimmel
It has been recently shown that neural networks can recover the geometric structure of a face from a single given image. A common denominator of most existing face geometry reconst…
Learning Detailed Face Reconstruction from a Single Image
Elad Richardson, Matan Sela, Roy Or-El +1
Reconstructing the detailed geometric structure of a face from a given image is a key to many computer vision and graphics applications, such as motion capture and reenactment. The…
3D Face Reconstruction by Learning from Synthetic Data
Elad Richardson, Matan Sela, Ron Kimmel
Fast and robust three-dimensional reconstruction of facial geometric structure from a single image is a challenging task with numerous applications. Here, we introduce a learning-b…
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques
Elad Richardson, Rom Herskovitz, Boris Ginsburg +1
We present SEBOOST, a technique for boosting the performance of existing stochastic optimization methods. SEBOOST applies a secondary optimization process in the subspace spanned b…