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Found 16 papers, 5 papers with code
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)
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.
Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking
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.
Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking
We propose a new Group Feature Selection method for Discriminative Correlation Filters (GFS-DCF) based visual object tracking.
Ranked #1 on
Visual Object Tracking
on VOT2017
Affine Non-negative Collaborative Representation Based Pattern Classification
Moreover, ANCR introduces an affine constraint to better represent the data from affine subspaces.
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.
A Unified Tensor-based Active Appearance Face Model
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 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
Dictionary Integration using 3D Morphable Face Models for Pose-invariant Collaborative-representation-based Classification
The paper presents a dictionary integration algorithm using 3D morphable face models (3DMM) for pose-invariant collaborative-representation-based face classification.
Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning
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.
Learning a Representation with the Block-Diagonal Structure for Pattern Classification
To counteract this problem, we propose an approach that learns Representation with Block-Diagonal Structure (RBDS) for robust image recognition.
An Accelerated Correlation Filter Tracker
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.
AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking
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.
DD-CNN: Depthwise Disout Convolutional Neural Network for Low-complexity Acoustic Scene Classification
This paper presents a Depthwise Disout Convolutional Neural Network (DD-CNN) for the detection and classification of urban acoustic scenes.
A Flatter Loss for Bias Mitigation in Cross-dataset Facial Age Estimation
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.
