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 • 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 • 12 Sep 2023 • Qiyu Sun, Huilin Chen, Meng Zheng, Ziyan Wu, Michael Felsberg, Yang Tang
Domain generalized semantic segmentation (DGSS) is a critical yet challenging task, where the model is trained only on source data without access to any target data.
1 code implementation • ICCV 2023 • Ruihao Xia, Chaoqiang Zhao, Meng Zheng, Ziyan Wu, Qiyu Sun, Yang Tang
However, limited by the low dynamic range of conventional cameras, images fail to capture structural details and boundary information in low-light conditions.
no code implementations • 12 May 2023 • Meng Zheng
This paper introduces and explores a new programming paradigm, Model-based Programming, designed to address the challenges inherent in applying deep learning models to real-world applications.
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 • 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 • AAAI -22 2022 • Zefang Zong, Meng Zheng, Yong Li, Depeng Jin
It is of great importance to efficiently provide high-quality solutions of cooperative PDP.
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, 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 • 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 • 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.
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 • 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 • 1 Jan 2021 • Hansen Wang, Zefang Zong, Tong Xia, Shuyu Luo, Meng Zheng, Depeng Jin, Yong Li
The large-scale vehicle routing problem is defined based on the classical VRP with usually more than one thousand customers.
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 • 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.
2 code implementations • CVPR 2020 • Wenqian Liu, Runze Li, Meng Zheng, Srikrishna Karanam, Ziyan Wu, Bir Bhanu, Richard J. Radke, Octavia Camps
We present methods to generate visual attention from the learned latent space, and also demonstrate such attention explanations serve more than just explaining VAE predictions.
no code implementations • CVPR 2019 • Meng Zheng, Srikrishna Karanam, Ziyan Wu, Richard J. Radke
We propose a new deep architecture for person re-identification (re-id).
no code implementations • 16 Aug 2018 • Meng Zheng, Srikrishna Karanam, Richard J. Radke
Designing real-world person re-identification (re-id) systems requires attention to operational aspects not typically considered in academic research.
no code implementations • 13 Oct 2017 • Siqi Nie, Meng Zheng, Qiang Ji
The major difficulty of learning and inference with deep directed models with many latent variables is the intractable inference due to the dependencies among the latent variables and the exponential number of latent variable configurations.