Amit Zohar
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View article: VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models Open
Despite tremendous recent progress, generative video models still struggle to capture real-world motion, dynamics, and physics. We show that this limitation arises from the conventional pixel reconstruction objective, which biases models t…
View article: Through-The-Mask: Mask-based Motion Trajectories for Image-to-Video Generation
Through-The-Mask: Mask-based Motion Trajectories for Image-to-Video Generation Open
We consider the task of Image-to-Video (I2V) generation, which involves transforming static images into realistic video sequences based on a textual description. While recent advancements produce photorealistic outputs, they frequently str…
View article: Movie Gen: A Cast of Media Foundation Models
Movie Gen: A Cast of Media Foundation Models Open
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 capabilities such as precise instruction-based video editing and ge…
View article: Video Editing via Factorized Diffusion Distillation
Video Editing via Factorized Diffusion Distillation Open
We introduce Emu Video Edit (EVE), a model that establishes a new state-of-the art in video editing without relying on any supervised video editing data. To develop EVE we separately train an image editing adapter and a video generation ad…
View article: Emu Edit: Precise Image Editing via Recognition and Generation Tasks
Emu Edit: Precise Image Editing via Recognition and Generation Tasks Open
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 ac…