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Eye Motion Matters for 3D Face Reconstruction

arXiv 2401.09677 ↗First posted 18 Jan 2024cs.CVcited by 0

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Abstract (arXiv)

Recent advances in single-image 3D face reconstruction have shown remarkable progress in various applications. Nevertheless, prevailing techniques tend to prioritize the global facial contour and expression, often neglecting the nuanced dynamics of the eye region. In response, we introduce an Eye Landmark Adjustment Module, complemented by a Local Dynamic Loss, designed to capture the dynamic features of the eyes area. Our module allows for flexible adjustment of landmarks, resulting in accurate recreation of various eye states. In this paper, we present a comprehensive evaluation of our approach, conducting extensive experiments on two datasets. The results underscore the superior performance of our approach, highlighting its significant contributions in addressing this particular challenge.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 32 references that are in the map. First posted on arXiv 18 Jan 2024.

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14 of 32 references.

References · 14

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  3. 2016Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networkscited by 895
  4. 2019Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Setcited by 481
  5. 2020Learning an Animatable Detailed 3D Face Model from In-The-Wild Imagescited by 475
  6. 2022EMOCA: Emotion Driven Monocular Face Capture and Animationcited by 254
  7. 2018Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Networkcited by 195
  8. 2019Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervisioncited by 176
  9. 2022Towards Metrical Reconstruction of Human Facescited by 165
  10. 2017MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstructioncited by 163
  11. 2018Face Alignment in Full Pose Range: A 3D Total Solutioncited by 147
  12. 2016Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Networkcited by 109
2 more
  1. 2022Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videoscited by 50
  2. 2022Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognitioncited by 24

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