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CoFaCo: Codificación de video de rostros parlantes generativos controlables

Xiaona Li, Xihua Sheng, Meng Wang

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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    PubMed
    Resumen
    Este resumen es generado por máquina.

    Este estudio presenta la Codificación de Video de Rostros Parlantes Generativos Controlables (CoFaCo), un nuevo marco para la compresión y control eficientes de video de rostros parlantes. CoFaCo integra la personalización de expresiones faciales y poses de cabeza directamente en el proceso de codificación de video para un rendimiento mejorado.

    Palabras clave:
    codificación de videorostros parlantescompresión de videoaprendizaje automáticovisión por computadorageneración de videoexpresión facialpose de cabeza

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    Área de la Ciencia:

    • Visión por Computadora
    • Compresión de Video
    • Aprendizaje Automático

    Sus antecedentes:

    • La codificación y el control eficientes de video de rostros parlantes son vitales para la comunicación moderna.
    • Los métodos actuales que aplican el control antes de la codificación carecen de una eficiencia de compresión satisfactoria.

    Objetivo del estudio:

    • Proponer un marco eficiente, Codificación de Video de Rostros Parlantes Generativos Controlables (CoFaCo), que integra el control en el proceso de codificación de video.
    • Permitir expresiones faciales y poses de cabeza personalizables por el usuario con una compresión mejorada.

    Principales métodos:

    • CoFaCo proyecta videos de rostros parlantes en representaciones de características compactas y semánticas.
    • Pérdidas sofisticadas desacoplan los códigos de dirección de pose y expresión para un control independiente.
    • Los generadores crean poses y expresiones controladas, con suavizado para la consistencia temporal.

    Principales resultados:

    • CoFaCo demuestra una eficiencia de compresión competitiva a tasas de bits ultrabajas.
    • El marco logra tareas efectivas de reconstrucción y control de video.
    • Los códigos desacoplados de pose y expresión mejoran la precisión del control y la estabilidad temporal.

    Conclusiones:

    • CoFaCo ofrece una solución eficiente para la codificación de video de rostros parlantes controlables.
    • El enfoque integrado avanza la comunicación de video facial con capacidades de control mejoradas.
    • Este marco proporciona información valiosa para futuros desarrollos en comunicación de video personalizada.