Neill D. F. Campbell

Orcid: 0000-0003-2130-4903

Affiliations:
  • University of Bath, Department of Computer Science, Bath, UK
  • University College London, Department of Computer Science, London, UK
  • University of Cambridge, Department of Engineering, Cambridge, UK


According to our database1, Neill D. F. Campbell authored at least 47 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Regularising Inverse Problems with Generative Machine Learning Models.
J. Math. Imaging Vis., January, 2024

2023

Likelihood-based Out-of-Distribution Detection with Denoising Diffusion Probabilistic Models.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
Compressed Sensing MRI Reconstruction Regularized by VAEs with Structured Image Covariance.
CoRR, 2022

Cell Anomaly Localisation using Structured Uncertainty Prediction Networks.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Learning Structured Gaussians to Approximate Deep Ensembles.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Aligned Multi-Task Gaussian Process.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation.
Remote. Sens., 2021

Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification.
CoRR, 2021

Active Latent Space Shape Model: A Bayesian Treatment of Shape Model Adaptation with an Application to Psoriatic Arthritis Radiographs.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020
Black-box density function estimation using recursive partitioning.
CoRR, 2020

Compositional uncertainty in deep Gaussian processes.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

The GAN That Warped: Semantic Attribute Editing With Unpaired Data.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Monotonic Gaussian Process Flows.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
MegaParallax: Casual 360° Panoramas with Motion Parallax.
IEEE Trans. Vis. Comput. Graph., 2019

Modulated Bayesian Optimization using Latent Gaussian Process Models.
CoRR, 2019

Monotonic Gaussian Process Flow.
CoRR, 2019

Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures.
Proceedings of the 36th International Conference on Machine Learning, 2019

Gaussian Process Latent Variable Alignment Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Sequence Alignment with Dirichlet Process Mixtures.
CoRR, 2018

Training VAEs Under Structured Residuals.
CoRR, 2018

Detection of dead standing Eucalyptus camaldulensis without tree delineation for managing biodiversity in native Australian forest.
Int. J. Appl. Earth Obs. Geoinformation, 2018

DiverseNet: When One Right Answer Is Not Enough.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Structured Uncertainty Prediction Networks.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation.
Proceedings of the Computer Vision - ACCV 2018, 2018

2017
Nonparametric Inference for Auto-Encoding Variational Bayes.
CoRR, 2017

Latent Gaussian Process Regression.
CoRR, 2017

Laplacian Pyramid of Conditional Variational Autoencoders.
Proceedings of the 14th European Conference on Visual Media Production (CVMP 2017), 2017

Responsive Action-based Video Synthesis.
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017

2016
Roto++: accelerating professional rotoscoping using shape manifolds.
ACM Trans. Graph., 2016

Fitting quadrics with a Bayesian prior.
Comput. Vis. Media, 2016

Improving and Optimising Visualisations of Full-waveform LiDAR Data.
Proceedings of the Computer Graphics & Visual Computing, 2016

Reading Between the Dots: Combining 3D Markers and FACS Classification for High-Quality Blendshape Facial Animation.
Proceedings of the 42nd Graphics Interface Conference, Victoria, BC, Canada, 1-3 June 2016, 2016

2015
Interactive Sketch-Driven Image Synthesis.
Comput. Graph. Forum, 2015

Direct, Dense, and Deformable: Template-Based Non-rigid 3D Reconstruction from RGB Video.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Modeling object appearance using Context-Conditioned Component Analysis.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Learning a manifold of fonts.
ACM Trans. Graph., 2014

Hierarchical Subquery Evaluation for Active Learning on a Graph.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

User Directed Multi-view-stereo.
Proceedings of the Computer Vision - ACCV 2014 Workshops, 2014

2013
Fully-Connected CRFs with Non-Parametric Pairwise Potential.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Patch Based Synthesis for Single Depth Image Super-Resolution.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Automatic Object Segmentation from Calibrated Images.
Proceedings of the Conference for Visual Media Production, 2011

2010
Automatic 3D object segmentation in multiple views using volumetric graph-cuts.
Image Vis. Comput., 2010

2008
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo.
Proceedings of the Computer Vision, 2008

2007
Automatic 3D Object Segmentation in Multiple Views using Volumetric Graph-Cuts.
Proceedings of the British Machine Vision Conference 2007, 2007


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