INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations
Yongming Zhu, Longhao Zhang, Zhengkun Rong, Tianshu Hu, Shuang Liang, Zhipeng Ge
2025年份
9顶会引用
摘要
Figure 1. We present INFP, an audio-driven interactive head generation framework for dyadic conversations. Given the dual-track audio in dyadic conversations and a single portrait image of arbitrary agent, our framework can dynamically synthesize verbal, non-verbal and interactive agent videos with lifelike facial expressions and rhythmic head pose movements. Additionally, our framework is lightweight yet powerful, making it practical in instant communication scenarios with acceptable latency, such as the video conferencing. INFP denotes our method is Interactive, Natural, Flash and Person-generic.
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引用它的顶会 Paper9
- SpeakerVid-5M: A Large-Scale High-Quality Dataset for Audio-Visual Dyadic Interactive Human GenerationYouliang Zhang, Zhaoyang Li, Duomin Wang, jiahe zhang 等ICLR 2026 · 被引用 30 次
- StreamAvatar: Streaming Diffusion Models for Real-Time Interactive Human AvatarsZhiyao Sun, Ziqiao Peng, Yifeng Ma, Yi Chen 等CVPR 2026 · 被引用 26 次
- Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural ConversationTaekyung Ki, Sangwon Jang, Jaehyeong Jo, Jaehong Yoon 等CVPR 2026 · 被引用 18 次
- DreamActor-M1: Holistic, Expressive and Robust Human Image Animation with Hybrid GuidanceYuxuan Luo, Zhengkun Rong, Lizhen Wang, Longhao Zhang 等ICCV 2025 · 被引用 5 次
- PolySLGen: Online Multimodal Speaking-Listening Reaction Generation in Polyadic InteractionZhi-Yi Lin, Thomas Markhorst, Jouh Yeong Chew, Xucong ZhangCVPR 2026 · 被引用 3 次
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