3 citations · 4 across the 3 of their papers we have counts for
7 papers
Diffusion Models Are Real-Time Game Engines
Dani Valevski, Yaniv Leviathan, Moab Arar +1
We present GameNGen, the first game engine powered entirely by a neural model that also enables real-time interaction with a complex environment over long trajectories at high qual…
Magic Insert: Style-Aware Drag-and-Drop
Nataniel Ruiz, Yuanzhen Li, Neal Wadhwa +4
We present Magic Insert, a method for dragging-and-dropping subjects from a user-provided image into a target image of a different style in a physically plausible manner while matc…
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion
Daniel Winter, Matan Cohen, Shlomi Fruchter +3
Diffusion models have revolutionized image editing but often generate images that violate physical laws, particularly the effects of objects on the scene, e.g., occlusions, shadows…
PALP: Prompt Aligned Personalization of Text-to-Image Models
Moab Arar, Andrey Voynov, Amir Hertz +5
Content creators often aim to create personalized images using personal subjects that go beyond the capabilities of conventional text-to-image models. Additionally, they may want t…
Style Aligned Image Generation via Shared Attention
Amir Hertz, Andrey Voynov, Shlomi Fruchter +1
Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts. However, controlling thes…
Curved Diffusion: A Generative Model With Optical Geometry Control
Andrey Voynov, Amir Hertz, Moab Arar +2
State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlook…