no code implementations • 11 Jan 2024 • Moab Arar, Andrey Voynov, Amir Hertz, Omri Avrahami, Shlomi Fruchter, Yael Pritch, Daniel Cohen-Or, Ariel Shamir
We term our approach prompt-aligned personalization.
1 code implementation • 4 Dec 2023 • Amir Hertz, Andrey Voynov, Shlomi Fruchter, Daniel Cohen-Or
Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts.
no code implementations • 29 Nov 2023 • Andrey Voynov, Amir Hertz, Moab Arar, Shlomi Fruchter, Daniel Cohen-Or
State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth.
1 code implementation • 16 Nov 2023 • Omri Avrahami, Amir Hertz, Yael Vinker, Moab Arar, Shlomi Fruchter, Ohad Fried, Daniel Cohen-Or, Dani Lischinski
Our quantitative analysis demonstrates that our method strikes a better balance between prompt alignment and identity consistency compared to the baseline methods, and these findings are reinforced by a user study.
no code implementations • 9 Jun 2023 • Alexandre Binninger, Amir Hertz, Olga Sorkine-Hornung, Daniel Cohen-Or, Raja Giryes
We present SENS, a novel method for generating and editing 3D models from hand-drawn sketches, including those of abstract nature.
no code implementations • ICCV 2023 • Amir Hertz, Kfir Aberman, Daniel Cohen-Or
We introduce Delta Denoising Score (DDS), a novel scoring function for text-based image editing that guides minimal modifications of an input image towards the content described in a target prompt.
no code implementations • 3 Mar 2023 • Shir Iluz, Yael Vinker, Amir Hertz, Daniel Berio, Daniel Cohen-Or, Ariel Shamir
A word-as-image is a semantic typography technique where a word illustration presents a visualization of the meaning of the word, while also preserving its readability.
4 code implementations • CVPR 2023 • Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, Daniel Cohen-Or
Our Null-text inversion, based on the publicly available Stable Diffusion model, is extensively evaluated on a variety of images and prompt editing, showing high-fidelity editing of real images.
Ranked #4 on Text-based Image Editing on PIE-Bench
7 code implementations • 2 Aug 2022 • Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, Daniel Cohen-Or
Editing is challenging for these generative models, since an innate property of an editing technique is to preserve most of the original image, while in the text-based models, even a small modification of the text prompt often leads to a completely different outcome.
Ranked #14 on Text-based Image Editing on PIE-Bench
1 code implementation • 15 Mar 2022 • Guy Tevet, Brian Gordon, Amir Hertz, Amit H. Bermano, Daniel Cohen-Or
MotionCLIP gains its unique power by aligning its latent space with that of the Contrastive Language-Image Pre-training (CLIP) model.
1 code implementation • 31 Jan 2022 • Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or
Neural implicit fields are quickly emerging as an attractive representation for learning based techniques.
4 code implementations • 18 Nov 2021 • Ron Mokady, Amir Hertz, Amit H. Bermano
Image captioning is a fundamental task in vision-language understanding, where the model predicts a textual informative caption to a given input image.
Ranked #1 on Image Captioning on Conceptual Captions
no code implementations • 11 Oct 2021 • Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or
The method drapes the source mesh over the target geometry and at the same time seeks to preserve the carefully designed characteristics of the source mesh.
no code implementations • 2 Sep 2021 • Oren Barkan, Omri Armstrong, Amir Hertz, Avi Caciularu, Ori Katz, Itzik Malkiel, Noam Koenigstein
The algorithmic advantages of GAM are explained in detail, and validated empirically, where it is shown that GAM outperforms its alternatives across various tasks and datasets.
1 code implementation • NeurIPS 2021 • Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or
Multilayer-perceptrons (MLP) are known to struggle with learning functions of high-frequencies, and in particular cases with wide frequency bands.
1 code implementation • 30 Jun 2020 • Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
Learning and synthesizing on local geometric patches enables a genus-oblivious framework, facilitating texture transfer between shapes of different genus.
1 code implementation • CVPR 2020 • Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
We present PointGMM, a neural network that learns to generate hGMMs which are characteristic of the shape class, and also coincide with the input point cloud.
1 code implementation • CVPR 2019 • Amir Hertz, Sharon Fogel, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
Many images shared over the web include overlaid objects, or visual motifs, such as text, symbols or drawings, which add a description or decoration to the image.
1 code implementation • 16 Sep 2018 • Rana Hanocka, Amir Hertz, Noa Fish, Raja Giryes, Shachar Fleishman, Daniel Cohen-Or
In this paper, we utilize the unique properties of the mesh for a direct analysis of 3D shapes using MeshCNN, a convolutional neural network designed specifically for triangular meshes.