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arXiv · 2602.13185

FlexAM: Flexible Appearance-Motion Decomposition for Versatile Video Generation Control

Mingzhi Sheng·Zekai Gu·Peng Li·Cheng Lin·Hao-Xiang Guo·Ying-Cong Chen·Yuan Liu
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Abstract

Effective and generalizable control in video generation remains a significant challenge. While many methods rely on ambiguous or task-specific signals, we argue that a fundamental disentanglement of "appearance" and "motion" provides a more robust and scalable pathway. We propose FlexAM, a unified framework built upon a novel 3D control signal. This signal represents video dynamics as a point cloud, introducing three key enhancements: multi-frequency positional encoding to distinguish fine-grained motion, depth-aware encoding, and a flexible control signal for balancing precision and generalization. This representation allows FlexAM to effectively disentangle appearance and motion, enabling a wide range of tasks including I2V/V2V editing, camera control, and spatial object editing. Extensive experiments demonstrate that FlexAM achieves superior performance across all evaluated tasks.

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Mingzhi Sheng, Zekai Gu, Peng Li, Cheng Lin, Hao-Xiang Guo, Ying-Cong Chen, Yuan Liu. 2026-08-17. FlexAM: Flexible Appearance-Motion Decomposition for Versatile Video Generation Control. https://arxiv.org/abs/2602.13185

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