mlsanityData to 7 Oct 2026

A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization

arXiv 2310.03205 ↗First posted 4 Oct 2023cs.CV cs.AIcited by 5

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Abstract (arXiv)

We propose NeuFace, a 3D face mesh pseudo annotation method on videos via neural re-parameterized optimization. Despite the huge progress in 3D face reconstruction methods, generating reliable 3D face labels for in-the-wild dynamic videos remains challenging. Using NeuFace optimization, we annotate the per-view/-frame accurate and consistent face meshes on large-scale face videos, called the NeuFace-dataset. We investigate how neural re-parameterization helps to reconstruct image-aligned facial details on 3D meshes via gradient analysis. By exploiting the naturalness and diversity of 3D faces in our dataset, we demonstrate the usefulness of our dataset for 3D face-related tasks: improving the reconstruction accuracy of an existing 3D face reconstruction model and learning 3D facial motion prior. Code and datasets will be available at https://neuface-dataset.github.io.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 62 of its 95 references that are in the map. First posted on arXiv 4 Oct 2023.

Builds on

62 of 95 references.

References · 62

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 0; 2025: 1; 2026: 1.

5 papers.