no code implementations • 19 Mar 2024 • Xiaoben Li, Mancheng Meng, Ziyan Wu, Terrence Chen, Fan Yang, Dinggang Shen
To facilitate the aggregation of the intra- and inter-view, we define a canonical parameter space, depicted by per-view camera pose and human pose and shape parameters ($\theta$ and $\beta$) of SMPL model, and propose a two-stage learning procedure.
no code implementations • 19 Mar 2024 • Xiaoben Li, Mancheng Meng, Ziyan Wu, Terrence Chen, Fan Yang, Dinggang Shen
Human mesh recovery from arbitrary multi-view images involves two characteristics: the arbitrary camera poses and arbitrary number of camera views.
no code implementations • 13 Mar 2024 • Xiao Chen, Shunan Zhang, Eric Z. Chen, Yikang Liu, Lin Zhao, Terrence Chen, Shanhui Sun
In artificial intelligence (AI), especially deep learning, data diversity and volume play a pivotal role in model development.
no code implementations • 13 Mar 2024 • Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao, Jian Xu, Qi Liu, Terrence Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun
The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processing time poses a challenge.
no code implementations • 13 Mar 2024 • Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao, Jian Xu, Qi Liu, Terrence Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun
Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring.
no code implementations • 9 Mar 2024 • Fan Yang, Benjamin Planche, Meng Zheng, Cheng Chen, Terrence Chen, Ziyan Wu
For decades, three-dimensional C-arm Cone-Beam Computed Tomography (CBCT) imaging system has been a critical component for complex vascular and nonvascular interventional procedures.
no code implementations • 5 Mar 2024 • Meng Zheng, Benjamin Planche, Xuan Gong, Fan Yang, Terrence Chen, Ziyan Wu
3D patient body modeling is critical to the success of automated patient positioning for smart medical scanning and operating rooms.
no code implementations • 4 Mar 2024 • Ange Lou, Benjamin Planche, Zhongpai Gao, Yamin Li, Tianyu Luan, Hao Ding, Terrence Chen, Jack Noble, Ziyan Wu
However, the straightforward decomposition of 4D dynamic scenes into multiple 2D plane-based representations proves insufficient for re-rendering high-fidelity scenes with complex motions.
no code implementations • 12 Feb 2024 • Zhongpai Gao, Huayi Zhou, Abhishek Sharma, Meng Zheng, Benjamin Planche, Terrence Chen, Ziyan Wu
The detection of human parts (e. g., hands, face) and their correct association with individuals is an essential task, e. g., for ubiquitous human-machine interfaces and action recognition.
no code implementations • 15 Dec 2023 • Yuchun Liu, Benjamin Planche, Meng Zheng, Zhongpai Gao, Pierre Sibut-Bourde, Fan Yang, Terrence Chen, Ziyan Wu
To effectively capture the interrelation between these entities and ensure precise, collision-free representations, our approach facilitates signaling between category-specific fields to adequately rectify shapes.
no code implementations • 2 Sep 2023 • Zihao Chen, Xiao Chen, Yikang Liu, Eric Z. Chen, Terrence Chen, Shanhui Sun
Cardiac Magnetic Resonance imaging (CMR) is the gold standard for assessing cardiac function.
no code implementations • 23 Mar 2023 • Zikui Cai, Zhongpai Gao, Benjamin Planche, Meng Zheng, Terrence Chen, M. Salman Asif, Ziyan Wu
We extensively evaluate our method using multiple datasets, demonstrating a higher de-identification rate and superior consistency compared to prior approaches in various downstream tasks.
1 code implementation • 11 Mar 2023 • Qin Liu, Meng Zheng, Benjamin Planche, Zhongpai Gao, Terrence Chen, Marc Niethammer, Ziyan Wu
Given a medical volume, a user first segments a slice (or several slices) via the interaction module and then propagates the segmentation(s) to the remaining slices.
no code implementations • 6 Feb 2023 • Yikang Liu, Eric Z. Chen, Xiao Chen, Terrence Chen, Shanhui Sun
Previous studies tackled these two problems separately, where super resolution methods tend to enhance Gibbs artifacts, whereas Gibbs ringing removal methods tend to blur the images.
no code implementations • 21 Jan 2023 • Eric Z. Chen, Chi Zhang, Xiao Chen, Yikang Liu, Terrence Chen, Shanhui Sun
Recon3DMLP improves HR 3D reconstruction and outperforms several existing CNN-based models under similar GPU memory consumption, which demonstrates that Recon3DMLP is a practical solution for HR 3D MRI reconstruction.
no code implementations • 3 Jan 2023 • Daniel H. Pak, Xiao Chen, Eric Z. Chen, Yikang Liu, Terrence Chen, Shanhui Sun
Deep learning (DL)-based methods have shown promising results for single-slice MR reconstruction, but the addition of SMS acceleration raises unique challenges due to the composite k-space signals and the resulting images with strong inter-slice artifacts.
no code implementations • 10 Dec 2022 • Xuan Gong, Liangchen Song, Meng Zheng, Benjamin Planche, Terrence Chen, Junsong Yuan, David Doermann, Ziyan Wu
To date, little attention has been given to multi-view 3D human mesh estimation, despite real-life applicability (e. g., motion capture, sport analysis) and robustness to single-view ambiguities.
no code implementations • 22 Oct 2022 • Lin Zhao, Xiao Chen, Eric Z. Chen, Yikang Liu, Dinggang Shen, Terrence Chen, Shanhui Sun
The proposed framework consists of a sampling mask generator for each image contrast and a reconstructor exploiting the inter-contrast correlations with a recurrent structure which enables the information sharing in a holistic way.
1 code implementation • 17 Oct 2022 • Mancheng Meng, Ziyan Wu, Terrence Chen, Xiran Cai, Xiang Sean Zhou, Fan Yang, Dinggang Shen
We categorize scene history information into two types: historical group trajectory and individual-surroundings interaction.
no code implementations • 16 Oct 2022 • Xuan Gong, Liangchen Song, Rishi Vedula, Abhishek Sharma, Meng Zheng, Benjamin Planche, Arun Innanje, Terrence Chen, Junsong Yuan, David Doermann, Ziyan Wu
We propose a privacy-preserving FL framework leveraging unlabeled public data for one-way offline knowledge distillation in this work.
no code implementations • 21 Sep 2022 • Liangchen Song, Xuan Gong, Benjamin Planche, Meng Zheng, David Doermann, Junsong Yuan, Terrence Chen, Ziyan Wu
We propose to regularize the estimated motion to be predictable.
no code implementations • 10 Sep 2022 • Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje
Federated Learning (FL) is a machine learning paradigm where local nodes collaboratively train a central model while the training data remains decentralized.
no code implementations • 10 Sep 2022 • Xuan Gong, Meng Zheng, Benjamin Planche, Srikrishna Karanam, Terrence Chen, David Doermann, Ziyan Wu
However, on synthetic dense correspondence maps (i. e., IUV) few have been explored since the domain gap between synthetic training data and real testing data is hard to address for 2D dense representation.
no code implementations • 21 Jul 2022 • Xiaoling Hu, Xiao Chen, Yikang Liu, Eric Z. Chen, Terrence Chen, Shanhui Sun
Additionally, the predicted point cloud guarantees boundary correspondence for sequential images, which contributes to the downstream tasks, such as the motion estimation of myocardium.
no code implementations • 12 Jul 2022 • Qin Liu, Meng Zheng, Benjamin Planche, Srikrishna Karanam, Terrence Chen, Marc Niethammer, Ziyan Wu
The goal of click-based interactive image segmentation is to obtain precise object segmentation masks with limited user interaction, i. e., by a minimal number of user clicks.
no code implementations • 6 Jun 2022 • Siyuan Dong, Eric Z. Chen, Lin Zhao, Xiao Chen, Yikang Liu, Terrence Chen, Shanhui Sun
During inference, the learned blurring transform can be inverted to a sharpening transform leveraging the network's invertibility.
no code implementations • CVPR 2022 • Hengtao Guo, Benjamin Planche, Meng Zheng, Srikrishna Karanam, Terrence Chen, Ziyan Wu
In order to obtain accurate target location information, clinicians have to either conduct frequent intraoperative scans, resulting in higher exposition of patients to radiations, or adopt proxy procedures (e. g., creating and using custom molds to keep patients in the exact same pose during both preoperative organ scanning and subsequent treatment.
1 code implementation • 23 Dec 2021 • Xi Ouyang, Srikrishna Karanam, Ziyan Wu, Terrence Chen, Jiayu Huo, Xiang Sean Zhou, Qian Wang, Jie-Zhi Cheng
However, doing this accurately will require a large amount of disease localization annotations by clinical experts, a task that is prohibitively expensive to accomplish for most applications.
no code implementations • 27 Jul 2021 • Runze Li, Srikrishna Karanam, Ren Li, Terrence Chen, Bir Bhanu, Ziyan Wu
We conduct a variety of experiments on standard video mesh recovery benchmark datasets such as Human3. 6M, MPI-INF-3DHP, and 3DPW, demonstrating the efficacy of our design of modeling local dynamics as well as establishing state-of-the-art results based on standard evaluation metrics.
Ranked #44 on 3D Human Pose Estimation on 3DPW
no code implementations • ICCV 2021 • Abhishek Aich, Meng Zheng, Srikrishna Karanam, Terrence Chen, Amit K. Roy-Chowdhury, Ziyan Wu
To alleviate these problems, we propose Spatio-Temporal Representation Factorization (STRF), a flexible new computational unit that can be used in conjunction with most existing 3D convolutional neural network architectures for re-ID.
Ranked #2 on Person Re-Identification on DukeMTMC-VideoReID
no code implementations • 13 Jul 2021 • Ren Li, Meng Zheng, Srikrishna Karanam, Terrence Chen, Ziyan Wu
Next, we present a simple baseline to address this problem that is scalable and can be easily used in conjunction with existing algorithms to improve their performance.
Ranked #1 on 3D Human Shape Estimation on SSP-3D (PVE-T metric)
no code implementations • 16 Jun 2021 • Junshen Xu, Eric Z. Chen, Xiao Chen, Terrence Chen, Shanhui Sun
The inference consists of iterative gradient updates similar to a conventional gradient descent optimizer but in a much faster way, because the neural ODE learns from the training data to adapt the gradient efficiently at each iteration.
no code implementations • 17 May 2021 • Eric Z. Chen, Yongquan Ye, Xiao Chen, Jingyuan Lyu, Zhongqi Zhang, Yichen Hu, Terrence Chen, Jian Xu, Shanhui Sun
We propose a deep learning framework for undersampled 3D MRI data reconstruction and apply it to MULTIPLEX MRI.
no code implementations • 17 May 2021 • Eric Z. Chen, Xiao Chen, Jingyuan Lyu, Qi Liu, Zhongqi Zhang, Yu Ding, Shuheng Zhang, Terrence Chen, Jian Xu, Shanhui Sun
To the best of our knowledge, this is the first work to evaluate the cine MRI with deep learning reconstruction for cardiac function analysis and compare it with other conventional methods.
no code implementations • CVPR 2021 • Yunhao Ge, Yao Xiao, Zhi Xu, Meng Zheng, Srikrishna Karanam, Terrence Chen, Laurent Itti, Ziyan Wu
Despite substantial progress in applying neural networks (NN) to a wide variety of areas, they still largely suffer from a lack of transparency and interpretability.
no code implementations • ICCV 2021 • Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje
Such decentralized training naturally leads to issues of imbalanced or differing data distributions among the local models and challenges in fusing them into a central model.
no code implementations • 25 Aug 2020 • Qiaoying Huang, Eric Z. Chen, Hanchao Yu, Yimo Guo, Terrence Chen, Dimitris Metaxas, Shanhui Sun
We also analyze thickness patterns on different cardiac pathologies with a standard clinical model and the results demonstrate the potential clinical value of our method for thickness based cardiac disease diagnosis.
no code implementations • 17 Aug 2020 • Pingjun Chen, Xiao Chen, Eric Z. Chen, Hanchao Yu, Terrence Chen, Shanhui Sun
A baseline dense motion tracker is trained to approximate the motion fields and then refined to estimate anatomy-aware motion fields under the weak supervision from the VAE.
no code implementations • 13 Aug 2020 • Meng Zheng, Srikrishna Karanam, Terrence Chen, Richard J. Radke, Ziyan Wu
We show that the resulting similarity models perform, and can be visually explained, better than the corresponding baseline models trained without these constraints.
no code implementations • 12 Aug 2020 • Eric Z. Chen, Xiao Chen, Jingyuan Lyu, Yuan Zheng, Terrence Chen, Jian Xu, Shanhui Sun
Real-time cardiac cine MRI does not require ECG gating in the data acquisition and is more useful for patients who can not hold their breaths or have abnormal heart rhythms.
no code implementations • 28 Jun 2020 • Hanchao Yu, Xiao Chen, Humphrey Shi, Terrence Chen, Thomas S. Huang, Shanhui Sun
In this paper, we propose Motion Pyramid Networks, a novel deep learning-based approach for accurate and efficient cardiac motion estimation.
no code implementations • 24 Jun 2020 • Eric Z. Chen, Terrence Chen, Shanhui Sun
We investigate several models based on three ODE solvers and compare models with fixed solvers and learned solvers.
no code implementations • CVPR 2020 • Hanchao Yu, Shanhui Sun, Haichao Yu, Xiao Chen, Honghui Shi, Thomas Huang, Terrence Chen
In clinical deployment, however, they suffer dramatic performance drops due to mismatched distributions between training and testing datasets, commonly encountered in the clinical environment.
no code implementations • ECCV 2020 • Georgios Georgakis, Ren Li, Srikrishna Karanam, Terrence Chen, Jana Kosecka, Ziyan Wu
In this work, we address this gap by proposing a new technique for regression of human parametric model that is explicitly informed by the known hierarchical structure, including joint interdependencies of the model.
no code implementations • 2 Dec 2019 • Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Shanhui Sun
We evaluate our model on the fastMRI knee and brain datasets and the results show that the proposed model outperforms other methods and can recover more details.
no code implementations • 18 Nov 2019 • Ren Li, Changjiang Cai, Georgios Georgakis, Srikrishna Karanam, Terrence Chen, Ziyan Wu
We consider the problem of human pose estimation.
no code implementations • 18 Nov 2019 • Meng Zheng, Srikrishna Karanam, Terrence Chen, Richard J. Radke, Ziyan Wu
While there has been substantial progress in learning suitable distance metrics, these techniques in general lack transparency and decision reasoning, i. e., explaining why the input set of images is similar or dissimilar.
no code implementations • 4 Aug 2018 • Elena Balashova, Vivek Singh, Jiangping Wang, Brian Teixeira, Terrence Chen, Thomas Funkhouser
We propose a new procedure to guide training of a data-driven shape generative model using a structure-aware loss function.
no code implementations • CVPR 2018 • Brian Teixeira, Vivek Singh, Terrence Chen, Kai Ma, Birgi Tamersoy, Yifan Wu, Elena Balashova, Dorin Comaniciu
Furthermore, the synthetic X-ray image is parametrized and can be manipulated by adjusting a set of body markers which are also generated during the X-ray image prediction.
no code implementations • 27 Feb 2017 • Benjamin Planche, Ziyan Wu, Kai Ma, Shanhui Sun, Stefan Kluckner, Terrence Chen, Andreas Hutter, Sergey Zakharov, Harald Kosch, Jan Ernst
Recent progress in computer vision has been dominated by deep neural networks trained over large amounts of labeled data.
no code implementations • CVPR 2016 • Venkatesh N. Murthy, Vivek Singh, Terrence Chen, R. Manmatha, Dorin Comaniciu
During the learning phase, starting from the root network node, DDN automatically builds a network that splits the data into disjoint clusters of classes which would be handled by the subsequent expert networks.
no code implementations • ICCV 2015 • Jiangping Wang, Kai Ma, Vivek Kumar Singh, Thomas Huang, Terrence Chen
3D human body shape matching has large potential on many real world applications, especially with the recent advances in the 3D range sensing technology.