activity
20202026
most citedAn Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

472 citations · 609 across the 28 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CV2024

Motion by Queries: Identity-Motion Trade-offs in Text-to-Video Generation

Yuval Atzmon, Rinon Gal, Yoad Tewel +2

Text-to-video diffusion models have shown remarkable progress in generating coherent video clips from textual descriptions. However, the interplay between motion, structure, and id…

cs.CV2024

Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models

Yoad Tewel, Rinon Gal, Dvir Samuel +3

Adding Object into images based on text instructions is a challenging task in semantic image editing, requiring a balance between preserving the original scene and seamlessly integ…

cs.CV2024★ 1 cited

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…

cs.CV2024

TurboEdit: Text-Based Image Editing Using Few-Step Diffusion Models

Gilad Deutch, Rinon Gal, Daniel Garibi +2

Diffusion models have opened the path to a wide range of text-based image editing frameworks. However, these typically build on the multi-step nature of the diffusion backwards pro…

cs.CV2024★ 12 cited

DiffUHaul: A Training-Free Method for Object Dragging in Images

Omri Avrahami, Rinon Gal, Gal Chechik +4

Text-to-image diffusion models have proven effective for solving many image editing tasks. However, the seemingly straightforward task of seamlessly relocating objects within a sce…

cs.CV2024

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,…

cs.CV2024

Consolidating Attention Features for Multi-view Image Editing

Or Patashnik, Rinon Gal, Daniel Cohen-Or +2

Large-scale text-to-image models enable a wide range of image editing techniques, using text prompts or even spatial controls. However, applying these editing methods to multi-view…

cs.CV2024

Training-Free Consistent Text-to-Image Generation

Yoad Tewel, Omri Kaduri, Rinon Gal +4

Text-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language. However, using these models to cons…