← Search

Oron Ashual

7 accepted papers

2024

Emu Edit: Precise Image Editing via Recognition and Generation Tasks

CVPR 2024highlight

Instruction-based image editing holds immense potential for a variety of applications as it enables users to perform any editing operation using a natural language instruction. However current models in this domain often struggle with accurately executing user instructions. We present Emu Edit a mul…

Cited by 124SourcePDFScholar
2023

Make-A-Video: Text-to-Video Generation without Text-Video Data

ICLR 2023poster

We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: learn what the world looks like and how it is described from paired text-image data, and learn how the world moves from un…

Cited by 1412SourcePDFScholar
2023

Text-To-4D Dynamic Scene Generation

ICML 2023poster

We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions. Our approach uses a 4D dynamic Neural Radiance Field (NeRF), which is optimized for scene appearance, density, and motion consistency by querying a Text-to-Video (T2V) diffusion-based…

2023

kNN-Diffusion: Image Generation via Large-Scale Retrieval

ICLR 2023poster

Recent text-to-image models have achieved impressive results. However, since they require large-scale datasets of text-image pairs, it is impractical to train them on new domains where data is scarce or not labeled. In this work, we propose using large-scale retrieval methods, in particular, efficie…

Cited by 139SourcePDFScholar
2022

Make-a-Scene: Scene-Based Text-to-Image Generation with Human Priors

ECCV 2022poster

"Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal gaps remain unanswered, limiting applicability and quality. We…

Cited by 575SourcePDFScholar