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Chris G. Willcocks
Chris G. Willcocks
Associate Professor, Durham University
Geverifieerd e-mailadres voor durham.ac.uk - Homepage
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Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models
S Bond-Taylor, A Leach, Y Long, CG Willcocks
IEEE transactions on pattern analysis and machine intelligence 44 (11), 7327 …, 2021
5352021
Using deep convolutional neural network architectures for object classification and detection within x-ray baggage security imagery
S Akcay, ME Kundegorski, CG Willcocks, TP Breckon
IEEE transactions on information forensics and security 13 (9), 2203-2215, 2018
3572018
Anoddpm: Anomaly detection with denoising diffusion probabilistic models using simplex noise
J Wyatt, A Leach, SM Schmon, CG Willcocks
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
2432022
Unit-ddpm: Unpaired image translation with denoising diffusion probabilistic models
H Sasaki, CG Willcocks, TP Breckon
arXiv preprint arXiv:2104.05358, 2021
1532021
Unmanned aerial vehicle visual detection and tracking using deep neural networks: A performance benchmark
BKS Isaac-Medina, M Poyser, D Organisciak, CG Willcocks, TP Breckon, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
762021
Mednerf: Medical neural radiance fields for reconstructing 3d-aware ct-projections from a single x-ray
A Corona-Figueroa, J Frawley, S Bond-Taylor, S Bethapudi, HPH Shum, ...
2022 44th annual international conference of the IEEE engineering in …, 2022
742022
Unleashing transformers: Parallel token prediction with discrete absorbing diffusion for fast high-resolution image generation from vector-quantized codes
S Bond-Taylor, P Hessey, H Sasaki, TP Breckon, CG Willcocks
European Conference on Computer Vision, 170-188, 2022
652022
Denoising Diffusion Probabilistic Models on SO (3) for Rotational Alignment
A Leach, SM Schmon, MT Degiacomi, CG Willcocks
International Conference on Learning Representations Workshop on Geometrical …, 2022
562022
Deep learning protein conformational space with convolutions and latent interpolations
VK Ramaswamy, SC Musson, CG Willcocks, MT Degiacomi
Physical Review X 11 (1), 011052, 2021
392021
Unsupervised region-based anomaly detection in brain MRI with adversarial image inpainting
B Nguyen, A Feldman, S Bethapudi, A Jennings, CG Willcocks
2021 IEEE 18th international symposium on biomedical imaging (ISBI), 1127-1131, 2021
342021
Multi-Scale Segmentation and Surface Fitting for Measuring 3-D Macular Holes
AV Nasrulloh, CG Willcocks, PTG Jackson, C Geenen, MS Habib, ...
IEEE Transactions on Medical Imaging 37 (2), 580-589, 2018
252018
Dynamic unary convolution in transformers
H Duan, Y Long, S Wang, H Zhang, CG Willcocks, L Shao
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (11 …, 2023
232023
Multi-view object detection using epipolar constraints within cluttered x-ray security imagery
BKS Isaac-Medina, CG Willcocks, TP Breckon
2020 25th International conference on pattern recognition (ICPR), 9889-9896, 2021
172021
Exact-nerf: An exploration of a precise volumetric parameterization for neural radiance fields
BKS Isaac-Medina, CG Willcocks, TP Breckon
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
162023
Feature-Varying Skeletonization
CG Willcocks, FWB Li
The Visual Computer 28 (6-8), 775-785, 2012
162012
Gradient origin networks
S Bond-Taylor, CG Willcocks
arXiv preprint arXiv:2007.02798, 2020
152020
-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
S Bond-Taylor, CG Willcocks
International Conference on Learning Representations, 2024
142024
Extracting 3D Parametric Curves from 2D images of Helical Objects
CG Willcocks, PTG Jackson, CJ Nelson, B Obara
IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (9), 1757-1769, 2017
132017
The relationship between curvilinear structure enhancement and ridge detection methods
HF Alhasson, CG Willcocks, SS Alharbi, A Kasim, B Obara
The Visual Computer 37, 2263-2283, 2021
92021
Deep generative modelling: A comparative review of VAEs, GANs, normalizing flows, energy-based and autoregressive models. arXiv 2021
S Bond-Taylor, A Leach, Y Long, CG Willcocks
arXiv preprint arXiv:2103.04922, 2022
82022
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Artikelen 1–20