Search Results for author:
Found 15 papers, 4 papers with code
Fake It Without Making It: Conditioned Face Generation for Accurate 3D Face Reconstruction
Our synthesis method conditions Stable Diffusion on depth maps sampled from the FLAME 3D Morphable Model (3DMM) of the human face, allowing us to generate a diverse set of shape-consistent facial images that is designed to be balanced in race and gender.
ID2image: Leakage of non-ID information into face descriptors and inversion from descriptors to images
Information about the environment (such as background and lighting) or changeable aspects of the face (such as pose, expression, presence of glasses, hat etc.)
Text2Face: A Multi-Modal 3D Face Model
We present the first 3D morphable modelling approach, whereby 3D face shape can be directly and completely defined using a textual prompt.
Neural Implicit Surface Reconstruction from Noisy Camera Observations
Representing 3D objects and scenes with neural radiance fields has become very popular over the last years.
Neural apparent BRDF fields for multiview photometric stereo
We propose to tackle the multiview photometric stereo problem using an extension of Neural Radiance Fields (NeRFs), conditioned on light source direction.
AestheticNet: Reducing bias in facial data sets under ethical considerations
Our experiments prove that human aesthetic judgements are usually biased.
Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild
To this end, we organise a competition that provides a new benchmark dataset that contains 2000 2D facial images of 135 subjects as well as their 3D ground truth face scans.
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
We present a new loss function, namely Wing loss, for robust facial landmark localisation with Convolutional Neural Networks (CNNs).
Ranked #1 on
Face Alignment
on 300W
(NME_inter-pupil (%, Common) metric)
3D Morphable Models as Spatial Transformer Networks
In this paper, we show how a 3D Morphable Model (i. e. a statistical model of the 3D shape of a class of objects such as faces) can be used to spatially transform input data as a module (a 3DMM-STN) within a convolutional neural network.
Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild
The framework has four stages: face detection, bounding box aggregation, pose estimation and landmark localisation.
Dynamic Attention-controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-set Sample Weighting
We present a new Cascaded Shape Regression (CSR) architecture, namely Dynamic Attention-Controlled CSR (DAC-CSR), for robust facial landmark detection on unconstrained faces.
Ranked #18 on
Face Alignment
on AFLW-19
A 3D Face Modelling Approach for Pose-Invariant Face Recognition in a Human-Robot Environment
Face analysis techniques have become a crucial component of human-machine interaction in the fields of assistive and humanoid robotics.
3D Face Tracking and Texture Fusion in the Wild
We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos.
A Multiresolution 3D Morphable Face Model and Fitting Framework
In this paper, we present the Surrey Face Model, a multi-resolution 3D Morphable Model that we make available to the public for non-commercial purposes.
Fitting 3D Morphable Models using Local Features
Our approach is unique in that we are the first to use local features to fit a Morphable Model.
