Follow-Your-Click: Open-domain Regional Image Animation via Short
  Prompts
Yue Ma Yingqing He Hongfa Wang Andong Wang Chenyang Qi Chengfei Cai Xiu Li Zhifeng Li Heung-Yeung Shum Wei Liu Qifeng Chen
Despite recent advances in image-to-video generation, better controllability
and local animation are less explored. Most existing image-to-video methods are
not locally aware and tend to move the entire scene. However, human artists may
need to control the movement of different objects or regions. Additionally,
current I2V methods require users not only to describe the target motion but
also to provide redundant detailed descriptions of frame contents. These two
issues hinder the practical utilization of current I2V tools. In this paper, we
propose a practical framework, named Follow-Your-Click, to achieve image
animation with a simple user click (for specifying what to move) and a short
motion prompt (for specifying how to move). Technically, we propose the
first-frame masking strategy, which significantly improves the video generation
quality, and a motion-augmented module equipped with a short motion prompt
dataset to improve the short prompt following abilities of our model. To
further control the motion speed, we propose flow-based motion magnitude
control to control the speed of target movement more precisely. Our framework
has simpler yet precise user control and better generation performance than
previous methods. Extensive experiments compared with 7 baselines, including
both commercial tools and research methods on 8 metrics, suggest the
superiority of our approach. Project Page: https://follow-your-click.github.io/