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ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Crossing the Uncanny Valley through Behavioral Authenticity: Synthesizing Photorealistic Avatars from Multi-Modal Personality Models.

Authors: Sorokin, Rodion; Nikolaichuk, Serhii;

Crossing the Uncanny Valley through Behavioral Authenticity: Synthesizing Photorealistic Avatars from Multi-Modal Personality Models.

Abstract

Despite decades of progress in photorealistic graphics, the "uncanny valley" remains a primary obstacle to the creation of believable digital humans. We posit that this problem is rooted not in a lack of visual fidelity, but in a lack of behavioral authenticity the cognitive dissonance that arises from a mismatch between an avatar's appearance and its lifeless behavior. This paper introduces a novel synthesis pipeline for photorealistic avatars that addresses this challenge. Our approach drives real-time facial animation not only from an audio stream for lip-syncing but from a stream of emotional metadata generated by a deep, multi-modal personality model. We present the complete pipeline, which includes the creation of a personalized, AI-driven rig that captures a user's unique micro-expressions and a mechanism for the perfect synchronization of vocal prosody, facial expressions, and articulation. We argue that this deep behavioral coherence, rather than graphical fidelity alone, is the key to crossing the uncanny valley and creating truly "living" digital interlocutors.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green