AnchorCrafter: Animate CyberAnchors Saling Your Products via Human-Object Interacting Video Generation

1Institute of Computing Technology, Chinese Academy of Sciences
2Meituan   3Great Bay University   4Tencent

*Indicates Equal Contribution

Abstract

The automatic generation of anchor-style product promotion videos presents promising opportunities in online commerce, advertising, and consumer engagement. However, this remains a challenging task despite significant advancements in pose-guided human video generation. In addressing this challenge, we identify the integration of human-object interactions (HOI) into pose-guided human video generation as a core issue. To this end, we introduce AnchorCrafter, a novel diffusion-based system designed to generate 2D videos featuring a target human and a customized object, achieving high visual fidelity and controllable interactions. Specifically, we propose two key innovations: the HOI-appearance perception, which enhances object appearance recognition from arbitrary multi-view perspectives and disentangles object and human appearance, and the HOI-motion injection, which enables complex human-object interactions by overcoming challenges in object trajectory conditioning and inter-occlusion management. Additionally, we introduce the HOI-region reweighting loss, a training objective that enhances the learning of object details. Extensive experiments demonstrate that our proposed system outperforms existing methods in preserving object appearance and shape awareness, while simultaneously maintaining consistency in human appearance and motion.

Methods

Training pipeline for AnchorCrafter (left) : Based on a video diffusion model, AnchorCrafter injects human and multi-view object references into the video via HOI-appearance perception. The motion is controlled through HOI-motion injection, with the training objective reweighted in the HOI region. HOI-appearance perception (right) : The feature of the target object fO is extracted through multi-view object feature fusion and combined with the human reference feature fH within a human- object dual adapter to achieve improved disentanglement results.

Results



Comparisons

Ablation

Video