Weidi Xie

I'm a research fellow at Visual Geometry Group, where I work on computer vision, deep learning, biomedical image analysis.

I completed my D.Phil in Engineering Science, University of Oxford, 2018,

Advisors: Professor Alison Noble (BioMedIA) and Professor Andrew Zisserman (VGG),

Thesis defence committees: Professor Andrea Vedaldi (Oxford) and Professor Daniel Rueckert (Imperial College London).

I was a recipient of the Excellence Award in 2018, from Department of Engineering Science, University of Oxford.
I was a recipient of Oxford-Google DeepMind Graduate Scholarships on Machine Learning and Biomedical Image Analysis.
I was a recipient of Magdalen Award from China Oxford Scholarship Fund (COSF)

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Research

I'm interested in computer vision, machine learning, biomedical image analysis.

2020

C14.   MAST: A Memory-Augmented Self-Supervised Tracker.
Zihang Lai, Erika Lu, Weidi Xie
In: Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Arxiv / Bibtex

C13.   VGG-Sound: A Large-Scale Audio-Visual Dataset.
Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Project Page / Code & Model / PDF / Arxiv

J6.   Low-Memory CNNs Enabling Real-Time Ultrasound Segmentation Towards Mobile Deployment.
Sagar Vaze, Weidi Xie, Ana Namburete.
In: IEEE Journal of Biomedical and Health Informatics, 2020. (Impact Factor: ~4.2)
Project Page / Code

J5.   VoxCeleb: Large-scale Speaker Verification in the Wild.
Arsha Nagrani*, Joon Son Chung*, Weidi Xie*, Andrew Zisserman. (* indicates equal contribution)
In: Computer Speech & Language, 2020. (Impact Factor: ~1.8)

2019

T1.   VoxSRC 2019: The first VoxCeleb Speaker Recognition Challenge.
Joon Son Chung, Arsha Nagrani, Ernesto Coto, Weidi Xie, Mitchell McLaren, Douglas A Reynolds, Andrew Zisserman.
Tech Report

C12.   Video Representation Learning by Dense Predictive Coding.
Tengda Han, Weidi Xie, Andrew Zisserman
In: 1st International Workshop on Large-scale Holistic Video Understanding, ICCV, 2019.   (Oral Presentation)
Project Page / Code / Arxiv / Bibtex

C11.   Self-supervised Learning for Video Correspondence Flow.
Zihang Lai, Weidi Xie
In: British Machine Vision Conference (BMVC), 2019.   (Oral Presentation)
Project Page / Arxiv / Bibtex

C10.   AutoCorrect: Deep Inductive Alignment of Noisy Geometric Annotations.
Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman.
In: British Machine Vision Conference (BMVC), 2019.   (Spotlight Presentation)
PDF / Bibtex

C9.   Geometry-Aware Corner Network for Video Object Detection from Static Cameras.
Dan Xu, Weidi Xie, Andrew Zisserman.
In: British Machine Vision Conference (BMVC), 2019.   (Oral Presentation)
PDF / Bibtex

C8.   Utterance-level Aggregation for Speaker Recognition in the Wild.
Weidi Xie, Arsha Nagrani, Joon Son Chung, Andrew Zisserman.
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019.   (Oral Presentation)
Project Page / Code & Model / Bibtex

2018

C7.   Comparator Networks.
Weidi Xie, Li Shen, Andrew Zisserman
In: European Conference on Computer Vision (ECCV), 2018.
Arxiv / Bibtex

C6.   Multicolumn Networks on Face Recognition.
Weidi Xie, Andrew Zisserman
In: British Machine Vision Conference (BMVC), 2018.
Arxiv / Code & Model / Bibtex

C5.   Class-Agnostic Counting.
Erika Lu, Weidi Xie, Andrew Zisserman
In: Asian Conference on Computer Vision (ACCV), 2018.
Project Page / Arxiv / Bibtex

C4.   VGGFace2: A Dataset for Recognising Faces Across Pose and Age.
Qiong Cao, Li Shen, Weidi Xie, Omkar M. Parkhi and Andrew Zisserman
In: IEEE International Conference on Automatic Face and Gesture Recognition (F&G), 2018.   (Oral Presentation)
Project Page / Arxiv / Bibtex

J4.   Omega-Net: Fully Automatic, Multi-View Cardiac MR Detection, Orientation, and Segmentation with Deep Neural Networks.
Weidi Xie*, Davis M. Vigneault*, Carolyn Y. Ho, David A. Bluemke and J. Alison Noble (* indicates equal contribution, joint first author)
In: Medical Image Analysis, Volume 48, Pages 95, August 2018. (Impact Factor: ~8.9)
Arxiv

J3.   VP-Nets: Efficient Automatic Localization of Key Brain Structures in 3D Fetal Neurosonography.
Ruobing Huang, Weidi Xie and J. Alison Noble
In: Medical Image Analysis, Volume 47, Pages 127, July 2018. (Impact Factor: ~8.9)

J2.   Fully-Automated Alignment of 3D Fetal Brain Ultrasound to a Canonical Reference Space Using Multi-task Learning.
Weidi Xie*, Ana I.L. Namburete*, Mohammad Yaqub, Andrew Zisserman and J. Alison Noble (* indicates equal contribution, joint first author)
In: Medical Image Analysis, Volume 46, Pages 1, May 2018. (Impact Factor: ~8.9)

2017

C3.   Feature Tracking Cardiac Magnetic Resonance via Deep Learning and Spline Optimization.
Davis M. Vigneaulta, Weidi Xie, David A. Bluemke and J. Alison Noble
In: Functional Imaging and Modelling of the Heart (FIMH), 2017.   (Best Poster Award)
Arxiv

C2.   Robust Regression of Brain Maturation from 3D Fetal Neurosonography using CRNs.
Ana I.L. Namburete, Weidi Xie and J. Alison Noble
In: MICCAI Workshop on Fetal and InFant Image analysis (FIFI), 2017.   (Best Paper Award)
Paper

2016

C1 & J1.   Microscopy Cell Counting and Detection with Fully Convolutional Regression Networks.
Weidi Xie, J. Alison Noble and Andrew Zisserman
In: MICCAI 1st Deep Learning Workshop, 2015.
In: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2016.   (Biannual Best Journal Article)
Paper / Code / Award

Dphil Thesis

Deep Neural Networks in Computer Vision and Biomedical Image Analysis.
Weidi Xie
Dphil Thesis, Unversity of Oxford, 2018.

Unpublished Papers

Layer Recurrent Neural Networks.
Weidi Xie, J. Alison Noble and Andrew Zisserman
Technical Report, 2017. URL

Service

Conference Review: CVPR, ICCV, ECCV, MICCAI, BMVC

Journal Review:

BMC Bioinformatics

ACM Computing Surveys

IEEE Transactions on Medical Imaging

International Journal of Computer Vision

IEEE Journal of Biomedical and Health Informatics

Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Biometrics, Behavior, and Identity Science