Deep learning architectures in physics-based character animation: a bibliometric mapping of research trajectories, 2016-2025

  • Alzet Rama 
    Universitas Negeri Padang
    Indonesia
  • Wiki Lofandri
    Universitas Negeri Padang
    Indonesia

Abstract

Perkembangan kecerdasan buatan (artificial intelligence/AI) telah mengubah lanskap produksi animasi secara fundamental, mulai dari sintesis gerak karakter, animasi wajah, hingga simulasi visual berbasis pembelajaran mendalam. Meskipun literatur pada domain ini berkembang pesat, pemetaan struktur intelektual dan arah evolusinya secara menyeluruh masih terbatas. Penelitian ini bertujuan memetakan struktur bibliometrik penelitian AI-assisted animation melalui analisis terhadap 983 dokumen yang diperoleh dari basis data Scopus periode 2016–2025, menggunakan kombinasi analisis deskriptif kuantitatif dan visualisasi jaringan kata kunci berbasis VOSviewer. Hasil analisis menunjukkan tren publikasi yang meningkat tajam sejak 2021, dengan dominasi kontribusi dari Tiongkok, Amerika Serikat, dan Korea Selatan, serta konsentrasi topik pada deep learning, reinforcement learning, dan character animation sebagai inti kluster keilmuan. Peta densitas dan jaringan kata kunci mengindikasikan pergeseran fokus riset dari pendekatan machine learning konvensional menuju arsitektur pembelajaran mendalam yang terintegrasi dengan reinforcement learning untuk pengendalian gerak fisik karakter (physics-based character control). Studi ini memberikan kontribusi berupa peta jalan tematik yang dapat menjadi rujukan bagi peneliti, praktisi industri animasi, maupun pengembang kebijakan riset teknologi kreatif dalam merumuskan agenda penelitian AI-assisted animation ke depan.

Keywords
  • AI-assisted animation, Bibliometrik, Deep learning, Character animation,
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