Search Results for author: Zhen-Hua Feng

Found 16 papers, 5 papers with code

A Flatter Loss for Bias Mitigation in Cross-dataset Facial Age Estimation

no code implementations20 Oct 2020 Ali Akbari, Muhammad Awais, Zhen-Hua Feng, Ammarah Farooq, Josef Kittler

Compared with existing loss functions, the lower gradient of the proposed loss function leads to the convergence of SGD to a better optimum point, and consequently a better generalisation.

Age Estimation Benchmarking +2

AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking

no code implementations27 May 2020 Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler

To this end, we propose a failure-aware system, realised by a Quality Prediction Network (QPN), based on convolutional and LSTM modules in the decision stage, enabling online reporting of potential tracking failures.

Benchmarking One-Shot Learning +1

An Accelerated Correlation Filter Tracker

no code implementations5 Dec 2019 Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler

Recent visual object tracking methods have witnessed a continuous improvement in the state-of-the-art with the development of efficient discriminative correlation filters (DCF) and robust deep neural network features.

Benchmarking Visual Object Tracking

Learning a Representation with the Block-Diagonal Structure for Pattern Classification

no code implementations23 Nov 2019 He-Feng Yin, Xiao-Jun Wu, Josef Kittler, Zhen-Hua Feng

To counteract this problem, we propose an approach that learns Representation with Block-Diagonal Structure (RBDS) for robust image recognition.

Benchmarking Classification +3

Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning

no code implementations19 Sep 2019 Cong Hu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler

To be more specific, the encoder-decoder structured generator is used to learn a pose disentangled face representation, and the encoder-decoder structured discriminator is tasked to perform real/fake classification, face reconstruction, determining identity and estimating face pose.

Benchmarking Face Generation +5

Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking

1 code implementation30 Jul 2018 Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler

The key innovations of the proposed method include adaptive spatial feature selection and temporal consistent constraints, with which the new tracker enables joint spatial-temporal filter learning in a lower dimensional discriminative manifold.

Benchmarking feature selection +2

Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild

no code implementations14 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.

3D Face Reconstruction 3D Reconstruction +1

Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks

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)

Data Augmentation Face Alignment

A Unified Tensor-based Active Appearance Face Model

no code implementations30 Dec 2016 Zhen-Hua Feng, Josef Kittler, William Christmas, Xiao-Jun Wu

To deal with this challenge, we present a Unified Tensor-based Active Appearance Model (UT-AAM) for jointly modelling the geometry and texture information of 2D faces.

Face Model

Dictionary Integration using 3D Morphable Face Models for Pose-invariant Collaborative-representation-based Classification

no code implementations1 Nov 2016 Xiaoning Song, Zhen-Hua Feng, Guosheng Hu, Josef Kittler, William Christmas, Xiao-Jun Wu

The paper presents a dictionary integration algorithm using 3D morphable face models (3DMM) for pose-invariant collaborative-representation-based face classification.

Classification General Classification

Fitting 3D Morphable Models using Local Features

1 code implementation8 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.


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