ActAvatar: Temporally-Aware Precise Action Control for Talking Avatars

Ziqiao Peng; Yi Chen; Yifeng Ma; Guozhen Zhang; Zhiyao Sun; Zixiang Zhou; Youliang Zhang; Zhengguang Zhou; Zhaoxin Fan; Hongyan Liu; Yuan Zhou; Qinglin Lu; Jun He

arXiv · 2512.19546

ActAvatar: Temporally-Aware Precise Action Control for Talking Avatars

Ziqiao Peng·Yi Chen·Yifeng Ma·Guozhen Zhang·Zhiyao Sun·Zixiang Zhou·Youliang Zhang·Zhengguang Zhou·Zhaoxin Fan·Hongyan Liu·Yuan Zhou·Qinglin Lu·Jun He

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Abstract

Despite significant advances in talking avatar generation, existing methods face critical challenges: insufficient text-following capability for diverse actions, lack of temporal alignment between actions and audio content, and dependency on additional control signals such as pose skeletons. We present ActAvatar, a framework that achieves phase-level precision in action control through textual guidance by capturing both action semantics and temporal context. Our approach introduces three core innovations: (1) Phase-Aware Cross-Attention (PACA), which decomposes prompts into a global base block and temporally-anchored phase blocks, enabling the model to concentrate on phase-relevant tokens for precise temporal-semantic alignment; (2) Progressive Audio-Visual Alignment, which aligns modality influence with the hierarchical feature learning process-early layers prioritize text for establishing action structure while deeper layers emphasize audio for refining lip movements, preventing modality interference; (3) A two-stage training strategy that first establishes robust audio-visual correspondence on diverse data, then injects action control through fine-tuning on structured annotations, maintaining both audio-visual alignment and the model's text-following capabilities. Extensive experiments demonstrate that ActAvatar significantly outperforms state-of-the-art methods in both action control and visual quality.

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Ziqiao Peng, Yi Chen, Yifeng Ma, Guozhen Zhang, Zhiyao Sun, Zixiang Zhou, Youliang Zhang, Zhengguang Zhou, Zhaoxin Fan, Hongyan Liu, Yuan Zhou, Qinglin Lu, Jun He. 2026-01-20. ActAvatar: Temporally-Aware Precise Action Control for Talking Avatars. https://arxiv.org/abs/2512.19546

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