10 citations · 13 across the 3 of their papers we have counts for
9 papers · 1 filter
The Effectiveness of Temporal Dependency in Deepfake Video Detection
Will Rowan, Nick Pears
Deepfakes are a form of synthetic image generation used to generate fake videos of individuals for malicious purposes. The resulting videos may be used to spread misinformation, re…
FatNet: A Feature-attentive Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
The application of deep learning to 3D point clouds is challenging due to its lack of order. Inspired by the point embeddings of PointNet and the edge embeddings of DGCNNs, we prop…
A Human Ear Reconstruction Autoencoder
Hao Sun, Nick Pears, Hang Dai
The ear, as an important part of the human head, has received much less attention compared to the human face in the area of computer vision. Inspired by previous work on monocular…
Towards a complete 3D morphable model of the human head
Stylianos Ploumpis, Evangelos Ververas, Eimear O' Sullivan +6
Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of…
SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
Deep neural networks have established themselves as the state-of-the-art methodology in almost all computer vision tasks to date. But their application to processing data lying on…
Combining 3D Morphable Models: A Large scale Face-and-Head Model
Stylianos Ploumpis, Haoyang Wang, Nick Pears +2
Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D surfaces of an object class. In this context, we identify an interesting question…