| Pre-training Strategies and Datasets for Facial Representation Learning | 0 | 0.34 | 2022 |
| EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers. | 0 | 0.34 | 2022 |
| High-Capacity Expert Binary Networks | 0 | 0.34 | 2021 |
| Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition | 0 | 0.34 | 2021 |
| Knowledge distillation via softmax regression representation learning | 0 | 0.34 | 2021 |
| IMPROVING MEMORY BANKS FOR UNSUPERVISED LEARNING WITH LARGE MINI-BATCH, CONSISTENCY AND HARD NEGATIVE MINING | 0 | 0.34 | 2021 |
| Faster, Better and More Detailed: 3D Face Reconstruction with Graph Convolutional Networks. | 0 | 0.34 | 2020 |
| Toward fast and accurate human pose estimation via soft-gated skip connections | 0 | 0.34 | 2020 |
| Fan-Face: A Simple Orthogonal Improvement To Deep Face Recognition | 0 | 0.34 | 2020 |
| Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning. | 0 | 0.34 | 2020 |
| Unsupervised Face Manipulation Via Hallucination | 0 | 0.34 | 2020 |
| Unsupervised Learning of Object Landmarks via Self-Training Correspondence | 0 | 0.34 | 2020 |
| Training binary neural networks with real-to-binary convolutions | 1 | 0.35 | 2020 |
| Animalweb: A Large-Scale Hierarchical Dataset Of Annotated Animal Faces | 0 | 0.34 | 2020 |
| T-Net: Parametrizing Fully Convolutional Nets With A Single High-Order Tensor | 0 | 0.34 | 2019 |
| Matrix and tensor decompositions for training binary neural networks. | 1 | 0.35 | 2019 |
| Improved training of binary networks for human pose estimation and image recognition. | 4 | 0.39 | 2019 |
| Object landmark discovery through unsupervised adaptation | 1 | 0.35 | 2019 |
| XNOR-Net++: Improved Binary Neural Networks | 2 | 0.36 | 2019 |
| A Functional Regression approach to Facial Landmark Tracking. | 1 | 0.35 | 2018 |
| Learning to Infer the Depth Map of a Hand from its Color Image | 1 | 0.35 | 2018 |
| Joint Action Unit localisation and intensity estimation through heatmap regression. | 1 | 0.35 | 2018 |
| Super-FAN: Integrated Facial Landmark Localization and Super-Resolution of Real-World Low Resolution Faces in Arbitrary Poses with GANs | 14 | 0.50 | 2018 |
| Pushing the boundaries of audiovisual word recognition using Residual Networks and LSTMs. | 1 | 0.35 | 2018 |
| Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture. | 2 | 0.39 | 2018 |
| Guest Editorial: The Computational Face. | 0 | 0.34 | 2018 |
| Hierarchical binary CNNs for landmark localization with limited resources. | 2 | 0.37 | 2018 |
| Fast and Exact Newton and Bidirectional Fitting of Active Appearance Models | 2 | 0.37 | 2017 |
| Frequency domain subpixel registration using HOG phase correlation. | 2 | 0.37 | 2017 |
| Combining Residual Networks With Lstms For Lipreading | 25 | 0.90 | 2017 |
| AFEW-VA database for valence and arousal estimation in-the-wild. | 18 | 0.77 | 2017 |
| Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images. | 3 | 0.38 | 2017 |
| Automated Risk Assessment for Scene Understanding and Domestic Robots Using RGB-D Data and 2.5D CNNs at a Patch Level | 0 | 0.34 | 2017 |
| 300 Faces In-The-Wild Challenge: database and results. | 0 | 0.34 | 2016 |
| Risk analysis for smart homes and domestic robots using robust shape and physics descriptors, and complex boosting techniques. | 1 | 0.37 | 2016 |
| ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016 | 1 | 0.36 | 2016 |
| 300 W: Special issue on facial landmark localisation "in-the-wild". | 0 | 0.34 | 2016 |
| The First Facial Landmark Tracking In-the-Wild Challenge: Benchmark and Results | 60 | 1.17 | 2015 |
| From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild | 22 | 0.67 | 2015 |
| Feature-based lucas-kanade and active appearance models. | 37 | 1.10 | 2015 |
| A 3D Scene Analysis Framework and Descriptors for Risk Evaluation | 1 | 0.35 | 2015 |
| HOG active appearance models | 13 | 0.59 | 2014 |
| Fast Newton active appearance models | 7 | 0.43 | 2014 |
| Gauss-Newton Deformable Part Models for Face Alignment In-the-Wild | 93 | 1.91 | 2014 |
| 300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge | 243 | 5.12 | 2013 |
| Euler Principal Component Analysis | 24 | 0.75 | 2013 |
| Optimization Problems for Fast AAM Fitting in-the-Wild | 82 | 1.74 | 2013 |
| Online learning and fusion of orientation appearance models for robust rigid object tracking. | 2 | 0.37 | 2013 |
| A Semi-automatic Methodology for Facial Landmark Annotation | 127 | 3.53 | 2013 |
| Subspace learning from image gradient orientations. | 86 | 1.84 | 2012 |
