315 citations · 553 across the 11 of their papers we have counts for
14 papers
RealMaster: Lifting Rendered Scenes into Photorealistic Video
Dana Cohen-Bar, Ido Sobol, Raphael Bensadoun +5
State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Fu…
Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials
Yawar Siddiqui, Tom Monnier, Filippos Kokkinos +8
We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared…
Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects
Raphael Bensadoun, Yanir Kleiman, Idan Azuri +4
The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and…
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht +4
Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somew…
Mosaic-SDF for 3D Generative Models
Lior Yariv, Omri Puny, Natalia Neverova +2
Current diffusion or flow-based generative models for 3D shapes divide to two: distilling pre-trained 2D image diffusion models, and training directly on 3D shapes. When training a…
SpaText: Spatio-Textual Representation for Controllable Image Generation
Omri Avrahami, Thomas Hayes, Oran Gafni +6
Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/…
Make-A-Video: Text-to-Video Generation without Text-Video Data
Uriel Singer, Adam Polyak, Thomas Hayes +10
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: le…
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Shelly Sheynin, Oron Ashual, Adam Polyak +4
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 w…
Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
Oran Gafni, Adam Polyak, Oron Ashual +3
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 gene…
Single-Shot Freestyle Dance Reenactment
Oran Gafni, Oron Ashual, Lior Wolf
The task of motion transfer between a source dancer and a target person is a special case of the pose transfer problem, in which the target person changes their pose in accordance…
Low Bandwidth Video-Chat Compression using Deep Generative Models
Maxime Oquab, Pierre Stock, Oran Gafni +9
To unlock video chat for hundreds of millions of people hindered by poor connectivity or unaffordable data costs, we propose to authentically reconstruct faces on the receiver's de…
Wish You Were Here: Context-Aware Human Generation
Oran Gafni, Lior Wolf
We present a novel method for inserting objects, specifically humans, into existing images, such that they blend in a photorealistic manner, while respecting the semantic context o…
Live Face De-Identification in Video
Oran Gafni, Lior Wolf, Yaniv Taigman
We propose a method for face de-identification that enables fully automatic video modification at high frame rates. The goal is to maximally decorrelate the identity, while having…
Vid2Game: Controllable Characters Extracted from Real-World Videos
Oran Gafni, Lior Wolf, Yaniv Taigman
We are given a video of a person performing a certain activity, from which we extract a controllable model. The model generates novel image sequences of that person, according to a…