no code implementations • 5 Mar 2023 • Will Rowan, Patrik Huber, Nick Pears, Andrew Keeling
We present the first 3D morphable modelling approach, whereby 3D face shape can be directly and completely defined using a textual prompt.
no code implementations • 2 Oct 2022 • Sarthak Gupta, Patrik Huber
Representing 3D objects and scenes with neural radiance fields has become very popular over the last years.
no code implementations • 14 Jul 2022 • Meghna Asthana, William A. P. Smith, Patrik Huber
We propose to tackle the multiview photometric stereo problem using an extension of Neural Radiance Fields (NeRFs), conditioned on light source direction.
no code implementations • 29 Sep 2021 • Michael Danner, Muhammad Awais Tanvir Rana, Thomas Weber, Tobias Gerlach, Patrik Huber, Matthias Rätsch, Josef Kittler
Our experiments prove that human aesthetic judgements are usually biased.
no code implementations • 14 Mar 2018 • Zhen-Hua Feng, Patrik Huber, Josef Kittler, Peter JB Hancock, Xiao-Jun Wu, Qijun Zhao, Paul Koppen, Matthias Rätsch
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.
6 code implementations • CVPR 2018 • Zhen-Hua Feng, Josef Kittler, Muhammad Awais, Patrik Huber, Xiao-Jun Wu
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)
1 code implementation • 23 Aug 2017 • Anil Bas, Patrik Huber, William A. P. Smith, Muhammad Awais, Josef Kittler
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.
no code implementations • 5 May 2017 • Zhen-Hua Feng, Josef Kittler, Muhammad Awais, Patrik Huber, Xiao-Jun Wu
The framework has four stages: face detection, bounding box aggregation, pose estimation and landmark localisation.
no code implementations • CVPR 2017 • Zhen-Hua Feng, Josef Kittler, William Christmas, Patrik Huber, Xiao-Jun Wu
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 #15 on Face Alignment on AFLW-19
no code implementations • 1 Jun 2016 • Michael Grupp, Philipp Kopp, Patrik Huber, Matthias Rätsch
Face analysis techniques have become a crucial component of human-machine interaction in the fields of assistive and humanoid robotics.
no code implementations • 22 May 2016 • Patrik Huber, Philipp Kopp, Matthias Rätsch, William Christmas, Josef Kittler
We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos.
1 code implementation • 1 Feb 2016 • Patrik Huber, Guosheng Hu, Rafael Tena, Pouria Mortazavian, Willem P. Koppen, William Christmas, Matthias Rätsch, Josef Kittler
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.
1 code implementation • 8 Mar 2015 • Patrik Huber, Zhen-Hua Feng, William Christmas, Josef Kittler, Matthias Rätsch
Our approach is unique in that we are the first to use local features to fit a Morphable Model.