Core Concepts
This paper presents ProbTalk, a unified probabilistic framework that jointly models facial expressions, hand gestures, and body poses to generate variable and coordinated holistic co-speech motions for 3D avatars.
Abstract
The paper addresses the problem of generating lifelike holistic co-speech motions for 3D avatars, focusing on two key aspects: variability and coordination.
The key highlights and insights are:
The authors propose ProbTalk, a unified probabilistic framework based on the variational autoencoder (VAE) architecture, to jointly model facial expressions, hand gestures, and body poses in speech.
ProbTalk incorporates three core designs:
a) Product quantization (PQ) to the VAE to enrich the representation of complex holistic motion.
b) A novel non-autoregressive model that embeds 2D positional encoding into the product-quantized representation to preserve the structural information.
c) A secondary stage to refine the preliminary prediction, further sharpening the high-frequency details.
The probabilistic nature of ProbTalk introduces essential variability to the resulting motions, allowing avatars to exhibit a wide range of movements for similar speech. The joint modeling improves the coordination, encouraging a harmonious alignment across various body parts.
Experimental results demonstrate that ProbTalk surpasses state-of-the-art methods in both qualitative and quantitative terms, with a particularly notable advancement in terms of realism.
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