Publications (22)
Inflating 2D Convolution Weights for Efficient Generation of 3D Medical Images
Yanbin Liu, Girish Dwivedi, Farid Boussaid +3
The generation of three-dimensional (3D) medical images has great application potential since it takes into account the 3D anatomical structure. Two problems prevent effective trai…
TCP Decoupling for Next Generation Communication System
Xiaohui Chen, Xiaowei Qin, Li Chen +7
In traditional networks, interfaces of network nodes are duplex. But, emerging communication technologies such as visible light communication, millimeter-wave communications, can o…
PMaF: Deep Declarative Layers for Principal Matrix Features
Zhiwei Xu, Hao Wang, Yanbin Liu +1
We explore two differentiable deep declarative layers, namely least squares on sphere (LESS) and implicit eigen decomposition (IED), for learning the principal matrix features (PMa…
UTS submission to Google YouTube-8M Challenge 2017
Linchao Zhu, Yanbin Liu, Yi Yang
In this paper, we present our solution to Google YouTube-8M Video Classification Challenge 2017. We leveraged both video-level and frame-level features in the submission. For video…
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection
Shaoshen Wang, Yanbin Liu, Ling Chen +1
Unsupervised anomaly detection (AD) is a challenging task in realistic applications. Recently, there is an increasing trend to detect anomalies with deep neural networks (DNN). How…
Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategies
Xiaodan Wang, Yanbin Liu, Shiqing Wu +4
The proliferation of online social networks has significantly reshaped the way individuals access and engage with information. While these platforms offer unprecedented connectivit…
Aligning Step-by-Step Instructional Diagrams to Video Demonstrations
Jiahao Zhang, Anoop Cherian, Yanbin Liu +3
Multimodal alignment facilitates the retrieval of instances from one modality when queried using another. In this paper, we consider a novel setting where such an alignment is betw…
Towards Superior Quantization Accuracy: A Layer-sensitive Approach
Feng Zhang, Yanbin Liu, Weihua Li +3
Large Vision and Language Models have exhibited remarkable human-like intelligence in tasks such as natural language comprehension, problem-solving, logical reasoning, and knowledg…
Mutual Exclusive Modulator for Long-Tailed Recognition
Haixu Long, Xiaolin Zhang, Yanbin Liu +2
The long-tailed recognition (LTR) is the task of learning high-performance classifiers given extremely imbalanced training samples between categories. Most of the existing works ad…
DCAF-Net: Dual-Channel Attentive Fusion Network for Lower Limb Motion Intention Prediction in Stroke Rehabilitation Exoskeletons
Liangshou Zhang, Yanbin Liu, Hanchi Liu +4
Rehabilitation exoskeletons have shown promising results in promoting recovery for stroke patients. Accurately and timely identifying the motion intentions of patients is a critica…
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park +4
The goal of few-shot learning is to learn a classifier that generalizes well even when trained with a limited number of training instances per class. The recently introduced meta-l…
3D Brain and Heart Volume Generative Models: A Survey
Yanbin Liu, Girish Dwivedi, Farid Boussaid +1
Generative models such as generative adversarial networks and autoencoders have gained a great deal of attention in the medical field due to their excellent data generation capabil…
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport
Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai +3
Estimating mutual information is an important statistics and machine learning problem. To estimate the mutual information from data, a common practice is preparing a set of paired…
MxML: Mixture of Meta-Learners for Few-Shot Classification
Minseop Park, Jungtaek Kim, Saehoon Kim +2
A meta-model is trained on a distribution of similar tasks such that it learns an algorithm that can quickly adapt to a novel task with only a handful of labeled examples. Most of…
Towards Understanding Gradient Approximation in Equality Constrained Deep Declarative Networks
Stephen Gould, Ming Xu, Zhiwei Xu +1
We explore conditions for when the gradient of a deep declarative node can be approximated by ignoring constraint terms and still result in a descent direction for the global loss…
Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting
Changlu Chen, Yanbin Liu, Chaoxi Niu +2
Foundation models have achieved remarkable success in natural language processing and computer vision, demonstrating strong capabilities in modeling complex patterns. While recent…
Multitask Deep Learning for Accurate Risk Stratification and Prediction of Next Steps for Coronary CT Angiography Patients
Juan Lu, Mohammed Bennamoun, Jonathon Stewart +5
Diagnostic investigation has an important role in risk stratification and clinical decision making of patients with suspected and documented Coronary Artery Disease (CAD). However,…
NeRFEditor: Differentiable Style Decomposition for Full 3D Scene Editing
Chunyi Sun, Yanbin Liu, Junlin Han +1
We present NeRFEditor, an efficient learning framework for 3D scene editing, which takes a video captured over 360° as input and outputs a high-quality, identity-preserving styliz…
Feature Robust Optimal Transport for High-dimensional Data
Mathis Petrovich, Chao Liang, Ryoma Sato +6
Optimal transport is a machine learning problem with applications including distribution comparison, feature selection, and generative adversarial networks. In this paper, we propo…
Pooling the Convolutional Layers in Deep ConvNets for Action Recognition
Shichao Zhao, Yanbin Liu, Yahong Han +1
Deep ConvNets have shown its good performance in image classification tasks. However it still remains as a problem in deep video representation for action recognition. The problem…
Trust-Aware Diversion for Data-Effective Distillation
Zhuojie Wu, Yanbin Liu, Xin Shen +2
Dataset distillation compresses a large dataset into a small synthetic subset that retains essential information. Existing methods assume that all samples are perfectly labeled, li…
AvatarBack: Back-Head Generation for Complete 3D Avatars from Front-View Images
Shiqi Xin, Xiaolin Zhang, Yanbin Liu +2
Recent advances in Gaussian Splatting have significantly boosted the reconstruction of head avatars, enabling high-quality facial modeling by representing an 3D avatar as a collect…