222 citations · 643 across the 42 of their papers we have counts for
42 papers
RenderIH: A Large-scale Synthetic Dataset for 3D Interacting Hand Pose Estimation
Lijun Li, Linrui Tian, Xindi Zhang +4
The current interacting hand (IH) datasets are relatively simplistic in terms of background and texture, with hand joints being annotated by a machine annotator, which may result i…
SEPT: Towards Efficient Scene Representation Learning for Motion Prediction
Zhiqian Lan, Yuxuan Jiang, Yao Mu +2
Motion prediction is crucial for autonomous vehicles to operate safely in complex traffic environments. Extracting effective spatiotemporal relationships among traffic elements is…
Learning Snippet-to-Motion Progression for Skeleton-based Human Motion Prediction
Xinshun Wang, Qiongjie Cui, Chen Chen +2
Existing Graph Convolutional Networks to achieve human motion prediction largely adopt a one-step scheme, which output the prediction straight from history input, failing to exploi…
M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization
Che Liu, Sibo Cheng, Chen Chen +5
Medical vision-language models enable co-learning and integrating features from medical imaging and clinical text. However, these models are not easy to train and the latent repres…
Hierarchical Task Network Planning for Facilitating Cooperative Multi-Agent Reinforcement Learning
Xuechen Mu, Hankz Hankui Zhuo, Chen Chen +3
Exploring sparse reward multi-agent reinforcement learning (MARL) environments with traps in a collaborative manner is a complex task. Agents typically fail to reach the goal state…
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model
Hasan Iqbal, Umar Khalid, Jing Hua +1
It can be challenging to identify brain MRI anomalies using supervised deep-learning techniques due to anatomical heterogeneity and the requirement for pixel-level labeling. Unsupe…
Former: Unified etrieval and eranking Transformer for Place Recognition
Sijie Zhu, Linjie Yang, Chen Chen +3
Visual Place Recognition (VPR) estimates the location of query images by matching them with images in a reference database. Conventional methods generally adopt aggregated CNN feat…
Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
Research in model-based reinforcement learning has made significant progress in recent years. Compared to single-agent settings, the exponential dimension growth of the joint state…
TimeBalance: Temporally-Invariant and Temporally-Distinctive Video Representations for Semi-Supervised Action Recognition
Ishan Rajendrakumar Dave, Mamshad Nayeem Rizve, Chen Chen +1
Semi-Supervised Learning can be more beneficial for the video domain compared to images because of its higher annotation cost and dimensionality. Besides, any video understanding t…
Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
In Model-based Reinforcement Learning (MBRL), model learning is critical since an inaccurate model can bias policy learning via generating misleading samples. However, learning an…
Networked Anti-Coordination Games Meet Graphical Dynamical Systems: Equilibria and Convergence
Zirou Qiu, Chen Chen, Madhav V. Marathe +4
Evolutionary anti-coordination games on networks capture real-world strategic situations such as traffic routing and market competition. In such games, agents maximize their utilit…
When Do Curricula Work in Federated Learning?
Saeed Vahidian, Sreevatsank Kadaveru, Woonjoon Baek +5
An oft-cited open problem of federated learning is the existence of data heterogeneity at the clients. One pathway to understanding the drastic accuracy drop in federated learning…
Quantifying the Individual Differences of Driver' Risk Perception with Just Four Interpretable Parameters
Chen Chen, Zhiqian Lan, Guojian Zhan +3
There will be a long time when automated vehicles are mixed with human-driven vehicles. Understanding how drivers assess driving risks and modelling their individual differences ar…
Language-Assisted Deep Learning for Autistic Behaviors Recognition
Andong Deng, Taojiannan Yang, Chen Chen +3
Correctly recognizing the behaviors of children with Autism Spectrum Disorder (ASD) is of vital importance for the diagnosis of Autism and timely early intervention. However, the o…
The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion)
Shuo Wang, Chen Qin, Chengyan Wang +12
The quality of cardiac magnetic resonance (CMR) imaging is susceptible to respiratory motion artifacts. The model robustness of automated segmentation techniques in face of real-wo…
Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks
Mahdi Morafah, Saeed Vahidian, Chen Chen +2
Though successful, federated learning presents new challenges for machine learning, especially when the issue of data heterogeneity, also known as Non-IID data, arises. To cope wit…
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces
Saeed Vahidian, Mahdi Morafah, Weijia Wang +4
Clustered federated learning (FL) has been shown to produce promising results by grouping clients into clusters. This is especially effective in scenarios where separate groups of…
Improved post-hoc probability calibration for out-of-domain MRI segmentation
Cheng Ouyang, Shuo Wang, Chen Chen +4
Probability calibration for deep models is highly desirable in safety-critical applications such as medical imaging. It makes output probabilities of deep networks interpretable, b…
GAMa: Cross-view Video Geo-localization
Shruti Vyas, Chen Chen, Mubarak Shah
The existing work in cross-view geo-localization is based on images where a ground panorama is matched to an aerial image. In this work, we focus on ground videos instead of images…
BANet: Motion Forecasting with Boundary Aware Network
Chen Zhang, Honglin Sun, Chen Chen +1
We propose a motion forecasting model called BANet, which means Boundary-Aware Network, and it is a variant of LaneGCN. We believe that it is not enough to use only the lane center…
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation
Chen Chen, Zeju Li, Cheng Ouyang +3
Convolutional neural networks (CNNs) have achieved remarkable segmentation accuracy on benchmark datasets where training and test sets are from the same domain, yet their performan…
Generative Myocardial Motion Tracking via Latent Space Exploration with Biomechanics-informed Prior
Chen Qin, Shuo Wang, Chen Chen +2
Myocardial motion and deformation are rich descriptors that characterize cardiac function. Image registration, as the most commonly used technique for myocardial motion tracking, i…
Multimodal Transformer for Nursing Activity Recognition
Momal Ijaz, Renato Diaz, Chen Chen
In an aging population, elderly patient safety is a primary concern at hospitals and nursing homes, which demands for increased nurse care. By performing nurse activity recognition…
Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees
Wenhan Cao, Jingliang Duan, Shengbo Eben Li +3
This paper proposes a primal-dual framework to learn a stable estimator for linear constrained estimation problems leveraging the moving horizon approach. To avoid the online compu…