Search Results for author: Omri Avrahami

Found 6 papers, 5 papers with code

Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields

1 code implementation22 Jun 2023 Ori Gordon, Omri Avrahami, Dani Lischinski

We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts, along with a 3D ROI box.

Break-A-Scene: Extracting Multiple Concepts from a Single Image

1 code implementation25 May 2023 Omri Avrahami, Kfir Aberman, Ohad Fried, Daniel Cohen-Or, Dani Lischinski

Text-to-image model personalization aims to introduce a user-provided concept to the model, allowing its synthesis in diverse contexts.

Complex Scene Breaking and Synthesis

SpaText: Spatio-Textual Representation for Controllable Image Generation

no code implementations CVPR 2023 Omri Avrahami, Thomas Hayes, Oran Gafni, Sonal Gupta, Yaniv Taigman, Devi Parikh, Dani Lischinski, Ohad Fried, Xi Yin

Due to lack of large-scale datasets that have a detailed textual description for each region in the image, we choose to leverage the current large-scale text-to-image datasets and base our approach on a novel CLIP-based spatio-textual representation, and show its effectiveness on two state-of-the-art diffusion models: pixel-based and latent-based.

Blended Latent Diffusion

1 code implementation6 Jun 2022 Omri Avrahami, Ohad Fried, Dani Lischinski

Our solution leverages a recent text-to-image Latent Diffusion Model (LDM), which speeds up diffusion by operating in a lower-dimensional latent space.

Image Inpainting text-guided-image-editing +1

GAN Cocktail: mixing GANs without dataset access

1 code implementation7 Jun 2021 Omri Avrahami, Dani Lischinski, Ohad Fried

In the second stage, we merge the rooted models by averaging their weights and fine-tuning them for each specific domain, using only data generated by the original trained models.

Transfer Learning

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