85 citations · 96 across the 5 of their papers we have counts for
7 papers
FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data
Oliver Boyne, Gwangbin Bae, James Charles +1
Surface reconstruction from multi-view images is a challenging task, with solutions often requiring a large number of sampled images with high overlap. We seek to develop a method…
FIND: An Unsupervised Implicit 3D Model of Articulated Human Feet
Oliver Boyne, James Charles, Roberto Cipolla
In this paper we present a high fidelity and articulated 3D human foot model. The model is parameterised by a disentangled latent code in terms of shape, texture and articulated po…
Discrete neural representations for explainable anomaly detection
Stanislaw Szymanowicz, James Charles, Roberto Cipolla
The aim of this work is to detect and automatically generate high-level explanations of anomalous events in video. Understanding the cause of an anomalous event is crucial as the r…
X-MAN: Explaining multiple sources of anomalies in video
Stanislaw Szymanowicz, James Charles, Roberto Cipolla
Our objective is to detect anomalies in video while also automatically explaining the reason behind the detector's response. In a practical sense, explainability is crucial for thi…
Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop
Benjamin Biggs, Oliver Boyne, James Charles +2
We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monocular internet images. The large variation in shape between dog breeds, significa…
Personalizing Human Video Pose Estimation
James Charles, Tomas Pfister, Derek Magee +2
We propose a personalized ConvNet pose estimator that automatically adapts itself to the uniqueness of a person's appearance to improve pose estimation in long videos. We make the…
Flowing ConvNets for Human Pose Estimation in Videos
Tomas Pfister, James Charles, Andrew Zisserman
The objective of this work is human pose estimation in videos, where multiple frames are available. We investigate a ConvNet architecture that is able to benefit from temporal cont…