The FineMotion entry to the GENEA Challenge 2023: DeepPhase for conversational gestures generation

Vladislav Korzun, Anna Beloborodova, Arkady Ilin
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引用次数: 1

Abstract

This paper describes FineMotion’s entry to the GENEA Challenge 2023. We explore the potential of DeepPhase embeddings by adapting neural motion controllers to conversational gesture generation. This is achieved by introducing a recurrent encoder for control features. We additionally use VQ-VAE codebook encoding of gestures to support dyadic setup. The resulting system generates stable realistic motion controllable by audio, text and interlocutor’s motion.
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FineMotion参加GENEA挑战赛2023:DeepPhase会话手势生成
本文描述了FineMotion参加2023年GENEA挑战赛的情况。我们通过使神经运动控制器适应会话手势生成来探索深度相位嵌入的潜力。这是通过为控制特性引入循环编码器来实现的。我们还使用VQ-VAE码本编码的手势来支持二元设置。由此产生的系统可以通过音频、文本和对话者的动作来控制稳定的逼真运动。
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Gesture Motion Graphs for Few-Shot Speech-Driven Gesture Reenactment The UEA Digital Humans entry to the GENEA Challenge 2023 Deciphering Entrepreneurial Pitches: A Multimodal Deep Learning Approach to Predict Probability of Investment The FineMotion entry to the GENEA Challenge 2023: DeepPhase for conversational gestures generation FEIN-Z: Autoregressive Behavior Cloning for Speech-Driven Gesture Generation
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