Search Results for author: Rinon Gal

Found 9 papers, 5 papers with code

"This is my unicorn, Fluffy": Personalizing frozen vision-language representations

no code implementations4 Apr 2022 Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon

We propose an architecture for solving PerVL that operates by extending the input vocabulary of a pretrained model with new word embeddings for the new personalized concepts.

Image Retrieval Semantic Segmentation +1

State-of-the-Art in the Architecture, Methods and Applications of StyleGAN

no code implementations28 Feb 2022 Amit H. Bermano, Rinon Gal, Yuval Alaluf, Ron Mokady, Yotam Nitzan, Omer Tov, Or Patashnik, Daniel Cohen-Or

Of these, StyleGAN offers a fascinating case study, owing to its remarkable visual quality and an ability to support a large array of downstream tasks.

Image Generation

Self-Conditioned Generative Adversarial Networks for Image Editing

no code implementations8 Feb 2022 Yunzhe Liu, Rinon Gal, Amit H. Bermano, Baoquan Chen, Daniel Cohen-Or

We compare our models to a wide range of latent editing methods, and show that by alleviating the bias they achieve finer semantic control and better identity preservation through a wider range of transformations.

Fairness

Stitch it in Time: GAN-Based Facial Editing of Real Videos

1 code implementation20 Jan 2022 Rotem Tzaban, Ron Mokady, Rinon Gal, Amit H. Bermano, Daniel Cohen-Or

The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing.

Facial Editing

HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing

1 code implementation30 Nov 2021 Yuval Alaluf, Omer Tov, Ron Mokady, Rinon Gal, Amit H. Bermano

In this work, we introduce this approach into the realm of encoder-based inversion.

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

2 code implementations2 Aug 2021 Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, Daniel Cohen-Or

Can a generative model be trained to produce images from a specific domain, guided by a text prompt only, without seeing any image?

Domain Adaptation Image Manipulation

LARGE: Latent-Based Regression through GAN Semantics

1 code implementation22 Jul 2021 Yotam Nitzan, Rinon Gal, Ofir Brenner, Daniel Cohen-Or

For modern generative frameworks, this semantic encoding manifests as smooth, linear directions which affect image attributes in a disentangled manner.

SWAGAN: A Style-based Wavelet-driven Generative Model

2 code implementations11 Feb 2021 Rinon Gal, Dana Cohen, Amit Bermano, Daniel Cohen-Or

In recent years, considerable progress has been made in the visual quality of Generative Adversarial Networks (GANs).

MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement

no code implementations25 Jul 2020 Rinon Gal, Amit Bermano, Hao Zhang, Daniel Cohen-Or

Our network encourages disentangled generation of semantic parts via two key ingredients: a root-mixing training strategy which helps decorrelate the different branches to facilitate disentanglement, and a set of loss terms designed with part disentanglement and shape semantics in mind.

3D Shape Generation Disentanglement

Cannot find the paper you are looking for? You can Submit a new open access paper.