Search Results for author: Jinming Duan

Found 41 papers, 20 papers with code

UniAV: Unified Audio-Visual Perception for Multi-Task Video Localization

1 code implementation4 Apr 2024 Tiantian Geng, Teng Wang, yanfu Zhang, Jinming Duan, Weili Guan, Feng Zheng

Video localization tasks aim to temporally locate specific instances in videos, including temporal action localization (TAL), sound event detection (SED) and audio-visual event localization (AVEL).

audio-visual event localization Event Detection +2

Low Rank Groupwise Deformations for Motion Tracking in Cardiac Cine MRI

no code implementations24 Mar 2024 Sean Rendell, Jinming Duan

Diffeomorphic image registration is a commonly used method to deform one image to resemble another.

Image Registration

Development of Automated Neural Network Prediction for Echocardiographic Left ventricular Ejection Fraction

no code implementations18 Mar 2024 Yuting Zhang, Boyang Liu, Karina V. Bunting, David Brind, Alexander Thorley, Andreas Karwath, Wenqi Lu, Diwei Zhou, Xiaoxia Wang, Alastair R. Mobley, Otilia Tica, Georgios Gkoutos, Dipak Kotecha, Jinming Duan

Within the pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained to segment the left ventricle (LV), before employing the area-length formulation based on the ellipsoid single-plane model to calculate LVEF values.

Ensemble Learning

Rediscovering BCE Loss for Uniform Classification

no code implementations12 Mar 2024 Qiufu Li, Xi Jia, Jiancan Zhou, Linlin Shen, Jinming Duan

We also propose the uniform classification accuracy as a metric to measure the model's performance in uniform classification.

Classification Face Recognition

Decoder-Only Image Registration

1 code implementation5 Feb 2024 Xi Jia, Wenqi Lu, Xinxing Cheng, Jinming Duan

For this, we propose a novel network architecture, termed LessNet in this paper, which contains only a learnable decoder, while entirely omitting the utilization of a learnable encoder.

Decoder Image Registration +1

Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems

no code implementations1 Jan 2024 Jintao Song, Wenqi Lu, Yunwen Lei, Yuchao Tang, Zhenkuan Pan, Jinming Duan

The Alternating Direction Method of Multipliers (ADMM) has gained significant attention across a broad spectrum of machine learning applications.

Deblurring Image Deblurring +2

ACT-Net: Anchor-context Action Detection in Surgery Videos

no code implementations5 Oct 2023 Luoying Hao, Yan Hu, Wenjun Lin, Qun Wang, Heng Li, Huazhu Fu, Jinming Duan, Jiang Liu

In this paper, to accurately detect fine-grained actions that happen at every moment, we propose an anchor-context action detection network (ACTNet), including an anchor-context detection (ACD) module and a class conditional diffusion (CCD) module, to answer the following questions: 1) where the actions happen; 2) what actions are; 3) how confidence predictions are.

Action Detection Denoising

Fourier-Net+: Leveraging Band-Limited Representation for Efficient 3D Medical Image Registration

1 code implementation6 Jul 2023 Xi Jia, Alexander Thorley, Alberto Gomez, Wenqi Lu, Dipak Kotecha, Jinming Duan

Instead of directly predicting a full-resolution displacement field, our Fourier-Net learns a low-dimensional representation of the displacement field in the band-limited Fourier domain which our model-driven decoder converts to a full-resolution displacement field in the spatial domain.

Decoder Medical Image Registration +1

Dense-Localizing Audio-Visual Events in Untrimmed Videos: A Large-Scale Benchmark and Baseline

1 code implementation CVPR 2023 Tiantian Geng, Teng Wang, Jinming Duan, Runmin Cong, Feng Zheng

To better adapt to real-life applications, in this paper we focus on the task of dense-localizing audio-visual events, which aims to jointly localize and recognize all audio-visual events occurring in an untrimmed video.

audio-visual event localization

UniFace: Unified Cross-Entropy Loss for Deep Face Recognition

1 code implementation ICCV 2023 Jiancan Zhou, Xi Jia, Qiufu Li, Linlin Shen, Jinming Duan

To bridge this gap, we design a UCE (Unified Cross-Entropy) loss for face recognition model training, which is built on the vital constraint that all the positive sample-to-class similarities shall be larger than the negative ones.

Face Recognition TAR

Category-Level 6D Object Pose Estimation with Flexible Vector-Based Rotation Representation

no code implementations9 Dec 2022 Wei Chen, Xi Jia, Zhongqun Zhang, Hyung Jin Chang, Linlin Shen, Jinming Duan, Ales Leonardis

The proposed rotation representation has two major advantages: 1) decoupled characteristic that makes the rotation estimation easier; 2) flexible length and rotated angle of the vectors allow us to find a more suitable vector representation for specific pose estimation task.

6D Pose Estimation using RGB Data Augmentation

Fourier-Net: Fast Image Registration with Band-limited Deformation

1 code implementation29 Nov 2022 Xi Jia, Joseph Bartlett, Wei Chen, Siyang Song, Tianyang Zhang, Xinxing Cheng, Wenqi Lu, Zhaowen Qiu, Jinming Duan

Specifically, instead of our Fourier-Net learning to output a full-resolution displacement field in the spatial domain, we learn its low-dimensional representation in a band-limited Fourier domain.

Ranked #3 on Medical Image Registration on OASIS (val dsc metric)

Decoder Medical Image Registration +1

U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?

1 code implementation7 Aug 2022 Xi Jia, Joseph Bartlett, Tianyang Zhang, Wenqi Lu, Zhaowen Qiu, Jinming Duan

On the public 3D IXI brain dataset for atlas-based registration, we show that the performance of the vanilla U-Net is already comparable with that of state-of-the-art transformer-based networks (such as TransMorph), and that the proposed LKU-Net outperforms TransMorph by using only 1. 12% of its parameters and 10. 8% of its mult-adds operations.

Image Registration Long-range modeling +1

Accelerated First Order Methods for Variational Imaging

1 code implementation6 Oct 2021 Joseph Bartlett, Jinming Duan

To overcome these drawbacks, we propose a novel adaption to Total Generalised Variation (TGV) regularisation called Total Smooth Variation (TSV), which retains edges and meanwhile does not produce results which contain staircase artefacts.

Denoising MRI Reconstruction +1

Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration

no code implementations26 Sep 2021 Alexander Thorley, Xi Jia, Hyung Jin Chang, Boyang Liu, Karina Bunting, Victoria Stoll, Antonio de Marvao, Declan P. O'Regan, Georgios Gkoutos, Dipak Kotecha, Jinming Duan

Recent developments in stochastic approaches based on deep learning have achieved sub-second runtimes for DiffIR with competitive registration accuracy, offering a fast alternative to conventional iterative methods.

Image Registration

Learning a Model-Driven Variational Network for Deformable Image Registration

no code implementations25 May 2021 Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan

We then propose two neural layers (i. e. warping layer and intensity consistency layer) to model the analytical solution and a residual U-Net to formulate the denoising problem (i. e. generalized denoising layer).

Denoising Image Registration

Complementary Time-Frequency Domain Networks for Dynamic Parallel MR Image Reconstruction

1 code implementation22 Dec 2020 Chen Qin, Jinming Duan, Kerstin Hammernik, Jo Schlemper, Thomas Küstner, René Botnar, Claudia Prieto, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert

The iterative model is embedded into a deep recurrent neural network which learns to recover the image via exploiting spatio-temporal redundancies in complementary domains.

De-aliasing Image Reconstruction

Geometry Constrained Weakly Supervised Object Localization

1 code implementation ECCV 2020 Weizeng Lu, Xi Jia, Weicheng Xie, Linlin Shen, Yicong Zhou, Jinming Duan

The detector predicts the object location defined by a set of coefficients describing a geometric shape (i. e. ellipse or rectangle), which is geometrically constrained by the mask produced by the generator.

Object Weakly-Supervised Object Localization

G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features

1 code implementation CVPR 2020 Wei Chen, Xi Jia, Hyung Jin Chang, Jinming Duan, Ales Leonardis

Third, via the predicted segmentation and translation, we transfer the fine object point cloud into a local canonical coordinate, in which we train a rotation localization network to estimate initial object rotation.

6D Pose Estimation 6D Pose Estimation using RGB +2

$Σ$-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction

1 code implementation18 Dec 2019 Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Daniel Rueckert

Purpose: To systematically investigate the influence of various data consistency layers, (semi-)supervised learning and ensembling strategies, defined in a $\Sigma$-net, for accelerated parallel MR image reconstruction using deep learning.

Image Enhancement Image Reconstruction +1

$Σ$-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction

1 code implementation11 Dec 2019 Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Kerstin Hammernik

We explore an ensembled $\Sigma$-net for fast parallel MR imaging, including parallel coil networks, which perform implicit coil weighting, and sensitivity networks, involving explicit sensitivity maps.

Image Reconstruction SSIM

dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance

1 code implementation24 Sep 2019 Jo Schlemper, Ilkay Oksuz, James R. Clough, Jinming Duan, Andrew P. King, Julia A. Schnabel, Joseph V. Hajnal, Daniel Rueckert

AUTOMAP is a promising generalized reconstruction approach, however, it is not scalable and hence the practicality is limited.

k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations

1 code implementation22 Jul 2019 Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam, Anthony Price, Joseph Hajnal, Daniel Rueckert

Experiments conducted on highly undersampled short-axis cardiac cine MRI scans demonstrate that our proposed method outperforms the current state-of-the-art dynamic MR reconstruction approaches both quantitatively and qualitatively.

Image Reconstruction

VS-Net: Variable splitting network for accelerated parallel MRI reconstruction

1 code implementation19 Jul 2019 Jinming Duan, Jo Schlemper, Chen Qin, Cheng Ouyang, Wenjia Bai, Carlo Biffi, Ghalib Bello, Ben Statton, Declan P. O'Regan, Daniel Rueckert

In this work, we propose a deep learning approach for parallel magnetic resonance imaging (MRI) reconstruction, termed a variable splitting network (VS-Net), for an efficient, high-quality reconstruction of undersampled multi-coil MR data.

MRI Reconstruction Rolling Shutter Correction

Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation

no code implementations5 Jul 2019 Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert

Deep unsupervised domain adaptation (UDA) aims to improve the performance of a deep neural network model on a target domain, using solely unlabelled target domain data and labelled source domain data.

Image Segmentation Medical Image Segmentation +3

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

no code implementations5 Jul 2019 Wenjia Bai, Chen Chen, Giacomo Tarroni, Jinming Duan, Florian Guitton, Steffen E. Petersen, Yike Guo, Paul M. Matthews, Daniel Rueckert

In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regression tasks.

Image Segmentation Position +4

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

1 code implementation28 Jun 2019 Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Antonio de Marvao, Ozan Oktay, Christian Ledig, Loic Le Folgoc, Konstantinos Kamnitsas, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert

At the highest level of this hierarchy, a two-dimensional latent space is simultaneously optimised to discriminate distinct clinical conditions, enabling the direct visualisation of the classification space.


A new nonlocal forward model for diffuse optical tomography

no code implementations3 Jun 2019 Wenqi Lu, Jinming Duan, Joshua Deepak Veesa, Iain B. Styles

The forward model in diffuse optical tomography (DOT) describes how light propagates through a turbid medium.

Image Reconstruction

Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography

no code implementations7 Jan 2019 Wenqi Lu, Jinming Duan, David Orive-Miguel, Lionel Herve, Iain B. Styles

Total variation (TV) is a powerful regularization method that has been widely applied in different imaging applications, but is difficult to apply to diffuse optical tomography (DOT) image reconstruction (inverse problem) due to complex and unstructured geometries, non-linearity of the data fitting and regularization terms, and non-differentiability of the regularization term.

Image Reconstruction

Tensor Based Second Order Variational Model for Image Reconstruction

no code implementations27 Sep 2016 Jinming Duan, Wil OC Ward, Luke Sibbett, Zhenkuan Pan, Li Bai

Second order total variation (SOTV) models have advantages for image reconstruction over their first order counterparts including their ability to remove the staircase artefact in the reconstructed image, but they tend to blur the reconstructed image.

Denoising Image Inpainting +1

Automated Segmentation of Retinal Layers from Optical Coherent Tomography Images Using Geodesic Distance

no code implementations7 Sep 2016 Jinming Duan, Christopher Tench, Irene Gottlob, Frank Proudlock, Li Bai

OCT image segmentation to localise retinal layer boundaries is a fundamental procedure for diagnosing and monitoring the progression of retinal and optical nerve disorders.

Image Segmentation Segmentation +1

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