MotionBooth: Motion-Aware Customized Text-to-Video Generation
Authors: name: Jianzong Wu, name: Xiangtai Li, name: Yanhong Zeng, name: Jiangning Zhang, name: Qianyu Zhou, name: Yining Li, name: Yunhai Tong, name: Kai Chen

In this work, we present MotionBooth, an innovative framework designed for
animating customized subjects with precise control over both object and camera
movements. By leveraging a few images of a specific object, we efficiently
fine-tune a text-to-video model to capture the object's shape and attributes
accurately. Our approach presents subject region loss and video preservation
loss to enhance the subject's learning performance, along with a subject token
cross-attention loss to integrate the customized subject with motion control
signals. Additionally, we propose training-free techniques for managing subject
and camera motions during inference. In particular, we utilize cross-attention
map manipulation to govern subject motion and introduce a novel latent shift
module for camera movement control as well. MotionBooth excels in preserving
the appearance of subjects while simultaneously controlling the motions in
generated videos. Extensive quantitative and qualitative evaluations
demonstrate the superiority and effectiveness of our method. Our project page
is at https://jianzongwu.github.io/projects/motionbooth