6.2k citations · 14.5k across the 98 of their papers we have counts for
126 papers
LLaVA-RE: Binary Image-Text Relevancy Evaluation with Multimodal Large Language Model
Tao Sun, Oliver Liu, JinJin Li +1
Multimodal generative AI usually involves generating image or text responses given inputs in another modality. The evaluation of image-text relevancy is essential for measuring res…
Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation
Samaneh Azadi, Akbar Shah, Thomas Hayes +2
Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models…
Text-Conditional Contextualized Avatars For Zero-Shot Personalization
Samaneh Azadi, Thomas Hayes, Akbar Shah +3
Recent large-scale text-to-image generation models have made significant improvements in the quality, realism, and diversity of the synthesized images and enable users to control t…
Text-To-4D Dynamic Scene Generation
Uriel Singer, Shelly Sheynin, Adam Polyak +8
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), whi…
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…