Search Results for author: Amir Hertz

Found 19 papers, 12 papers with code

Style Aligned Image Generation via Shared Attention

1 code implementation4 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.

Image Generation

AnyLens: A Generative Diffusion Model with Any Rendering Lens

no code implementations29 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.

Text Segmentation

The Chosen One: Consistent Characters in Text-to-Image Diffusion Models

1 code implementation16 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.

Consistent Character Generation Story Visualization

SENS: Part-Aware Sketch-based Implicit Neural Shape Modeling

no code implementations9 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.

Delta Denoising Score

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.

Denoising Image-to-Image Translation +2

Word-As-Image for Semantic Typography

no code implementations3 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.

Null-text Inversion for Editing Real Images using Guided Diffusion Models

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.

Image Generation Text-based Image Editing

Prompt-to-Prompt Image Editing with Cross Attention Control

7 code implementations2 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.

Image Generation Text-based Image Editing

MotionCLIP: Exposing Human Motion Generation to CLIP Space

1 code implementation15 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.

Disentanglement Motion Interpolation

SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation

1 code implementation31 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.

3D Shape Modeling

ClipCap: CLIP Prefix for Image Captioning

4 code implementations18 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.

Image Captioning Language Modelling

Mesh Draping: Parametrization-Free Neural Mesh Transfer

no code implementations11 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.

GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps

no code implementations2 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.


SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization

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.

Representation Learning

Deep Geometric Texture Synthesis

1 code implementation30 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.

Image Generation Texture Synthesis

PointGMM: a Neural GMM Network for Point Clouds

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.

Blind Visual Motif Removal from a Single Image

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.

MeshCNN: A Network with an Edge

1 code implementation16 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.

3D Part Segmentation Cube Engraving Classification

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