747 citations · 872 across the 14 of their papers we have counts for
17 papers
Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Prompts
Feng Liang, Haoyu Ma, Zecheng He +10
Video personalization, which generates customized videos using reference images, has gained significant attention. However, prior methods typically focus on single-concept personal…
Generating Multi-Image Synthetic Data for Text-to-Image Customization
Nupur Kumari, Xi Yin, Jun-Yan Zhu +2
Customization of text-to-image models enables users to insert new concepts or objects and generate them in unseen settings. Existing methods either rely on comparatively expensive…
MotiF: Making Text Count in Image Animation with Motion Focal Loss
Shijie Wang, Samaneh Azadi, Rohit Girdhar +3
Text-Image-to-Video (TI2V) generation aims to generate a video from an image following a text description, which is also referred to as text-guided image animation. Most existing m…
Movie Gen: A Cast of Media Foundation Models
Adam Polyak, Amit Zohar, Andrew Brown +85
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…
Motion-Conditioned Image Animation for Video Editing
Wilson Yan, Andrew Brown, Pieter Abbeel +2
We introduce MoCA, a Motion-Conditioned Image Animation approach for video editing. It leverages a simple decomposition of the video editing problem into image editing followed by…
Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning
Rohit Girdhar, Mannat Singh, Andrew Brown +7
We present Emu Video, a text-to-video generation model that factorizes the generation into two steps: first generating an image conditioned on the text, and then generating a video…