mlsanityData to 14 Oct 2026

Controllable Radiance Fields for Dynamic Face Synthesis

arXiv 2210.05825 ↗First posted 11 Oct 2022cs.CV cs.AIcited by 8

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Abstract (arXiv)

Recent work on 3D-aware image synthesis has achieved compelling results using advances in neural rendering. However, 3D-aware synthesis of face dynamics hasn't received much attention. Here, we study how to explicitly control generative model synthesis of face dynamics exhibiting non-rigid motion (e.g., facial expression change), while simultaneously ensuring 3D-awareness. For this we propose a Controllable Radiance Field (CoRF): 1) Motion control is achieved by embedding motion features within the layered latent motion space of a style-based generator; 2) To ensure consistency of background, motion features and subject-specific attributes such as lighting, texture, shapes, albedo, and identity, a face parsing net, a head regressor and an identity encoder are incorporated. On head image/video data we show that CoRFs are 3D-aware while enabling editing of identity, viewing directions, and motion.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 62 of its 77 references that are in the map. First posted on arXiv 11 Oct 2022.

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62 of 77 references.

References · 62

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38 more
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50 most cited of 62 All 62 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 1; 2025: 2; 2026: 1.

8 papers.