mlsanityData to 7 Oct 2026

FLNeRF: 3D Facial Landmarks Estimation in Neural Radiance Fields

arXiv 2211.11202 ↗First posted 21 Nov 2022cs.CV cs.GRcited by 2

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Abstract (arXiv)

This paper presents the first significant work on directly predicting 3D face landmarks on neural radiance fields (NeRFs). Our 3D coarse-to-fine Face Landmarks NeRF (FLNeRF) model efficiently samples from a given face NeRF with individual facial features for accurate landmarks detection. Expression augmentation is applied to facial features in a fine scale to simulate large emotions range including exaggerated facial expressions (e.g., cheek blowing, wide opening mouth, eye blinking) for training FLNeRF. Qualitative and quantitative comparison with related state-of-the-art 3D facial landmark estimation methods demonstrate the efficacy of FLNeRF, which contributes to downstream tasks such as high-quality face editing and swapping with direct control using our NeRF landmarks. Code and data will be available. Github link: https://github.com/ZHANG1023/FLNeRF.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 74 of its 115 references that are in the map. First posted on arXiv 21 Nov 2022.

Builds on

74 of 115 references.

References · 74

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38 more
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50 most cited of 74 All 74 (JSON)

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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023HQ3DAvatar: High Quality Controllable 3D Head Avatarcited by 9
  2. 2024FaceLift: Semi-supervised 3D Facial Landmark Localizationcited by 2