MoCoGAN: Decomposing Motion and Content for Video Generation

Understand

Visual signals in a video can be divided into content and motion.

• While content specifies which objects are in the video, motion describes their dynamics.
• Based on this prior, we propose the Motion and Content decomposed Generative Adversarial Network (MoCoGAN) framework for video generation.
• The proposed framework generates a video by mapping a sequence of random vectors to a sequence of video frames.