Filmmaking and animation production often require sophisticated techniques
for coordinating camera transitions and object movements, typically involving
labor-intensive real-world capturing. Despite advancements in generative AI for
video creation, achieving precise control over motion for interactive video
asset generation remains challenging. To this end, we propose Image Conductor,
a method for precise control of camera transitions and object movements to
generate video assets from a single image. An well-cultivated training strategy
is proposed to separate distinct camera and object motion by camera LoRA
weights and object LoRA weights. To further address cinematographic variations
from ill-posed trajectories, we introduce a camera-free guidance technique
during inference, enhancing object movements while eliminating camera
transitions. Additionally, we develop a trajectory-oriented video motion data
curation pipeline for training. Quantitative and qualitative experiments
demonstrate our method's precision and fine-grained control in generating
motion-controllable videos from images, advancing the practical application of
interactive video synthesis. Project webpage available at
this https URL

提出了一种从单张图像生成视频资产的方法，通过 Image Conductor 实现了摄像机转换和物体移动的精确控制，并通过训练策略、引导技术和数据处理流程进一步改进，展示了在交互式视频合成中实现精准控制的效果。