Search Results for author:
Found 27 papers, 9 papers with code
Konwledge-Enabled Diagnosis Assistant Based on Obstetric EMRs and Knowledge Graph
In this paper, we treat the diagnosis assistant as a multi-label classification task and propose a Knowledge-Enabled Diagnosis Assistant (KEDA) model for the obstetric diagnosis assistant.
Does Deep Learning REALLY Outperform Non-deep Machine Learning for Clinical Prediction on Physiological Time Series?
In this paper, we systematically examine the performance of machine learning models for the clinical prediction task based on the EHR, especially physiological time series.
Transfering Low-Frequency Features for Domain Adaptation
Previous unsupervised domain adaptation methods did not handle the cross-domain problem from the perspective of frequency for computer vision.
FusePose: IMU-Vision Sensor Fusion in Kinematic Space for Parametric Human Pose Estimation
On Total Capture dataset, KineFuse surpasses previous state-of-the-art which uses IMU only for testing by 8. 6\%.
Ranked #2 on
3D Human Pose Estimation
on Total Capture
Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder
This paper attempts to tackle the item cold-start problem by generating enhanced warmed-up ID embeddings for cold items with historical data and limited interaction records.
ETAD: Training Action Detection End to End on a Laptop
We propose to sequentially forward the snippet frame through the video encoder, and backward only a small necessary portion of gradients to update the encoder.
Learning-Based Framework for Camera Calibration with Distortion Correction and High Precision Feature Detection
Therefore, in this paper, we propose a hybrid camera calibration framework which combines learning-based approaches with traditional methods to handle these bottlenecks.
Pruning-aware Sparse Regularization for Network Pruning
MaskSparsity imposes the fine-grained sparse regularization on the specific filters selected by a pruning mask, rather than all the filters of the model.
Estimate Metabolite Taxonomy and Structure with a Fragment-Centered Database and Fragment Network
Metabolite structure identification has become the major bottleneck of the mass spectrometry based metabolomics research.
Adaptive Tree Wasserstein Minimization for Hierarchical Generative Modeling
In this work, we consider OT over tree metrics, which is more general than the sliced Wasserstein and includes the sliced Wasserstein as a special case, and we propose a fast minimization algorithm in $O(n)$ for the optimal Wasserstein-1 transport plan between two distributions in the tree structure.
An End to End Network Architecture for Fundamental Matrix Estimation
In this paper, we present a novel end-to-end network architecture to estimate fundamental matrix directly from stereo images.
Semi-Supervised Bilingual Lexicon Induction with Two-way Interaction
In this paper, we propose a new semi-supervised BLI framework to encourage the interaction between the supervised signal and unsupervised alignment.
Task Decoupled Knowledge Distillation For Lightweight Face Detectors
This method decouples the distillation task of face detection into two subtasks, i. e., the classification distillation subtask and the regression distillation subtask.
A Relaxed Matching Procedure for Unsupervised BLI
Recently unsupervised Bilingual Lexicon Induction (BLI) without any parallel corpus has attracted much research interest.
Parameter Sharing Decoder Pair for Auto Composing
Auto Composing is an active and appealing research area in the past few years, and lots of efforts have been put into inventing more robust models to solve this problem.
Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2
This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2019 Task 1 (\textbf{temporal action proposal generation}) and Task 2 (\textbf{temporal action localization/detection}).
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection
EdgeStereo also achieves comparable generalization performance for disparity estimation because of the incorporation of edge cues.
A Tangent Distance Preserving Dimensionality Reduction Algorithm
TDPM uses tangent distance instead of geodesic distance, and then applies MDS to the tangent distance matrix to map the manifold into a low dimensional space in which we can get its nonlinear structure.
Cascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization
Weakly supervised temporal action localization, which aims at temporally locating action instances in untrimmed videos using only video-level class labels during training, is an important yet challenging problem in video analysis.
Discriminative Representation Combinations for Accurate Face Spoofing Detection
Secondly we utilize the SSD, which is a deep learning framework for detection, to excavate context cues and conduct end-to-end face presentation attack detection.
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
Temporal action proposal generation is an important yet challenging problem, since temporal proposals with rich action content are indispensable for analysing real-world videos with long duration and high proportion irrelevant content.
Ranked #2 on
Temporal Action Proposal Generation
on THUMOS' 14
EdgeStereo: A Context Integrated Residual Pyramid Network for Stereo Matching
Recent convolutional neural networks, especially end-to-end disparity estimation models, achieve remarkable performance on stereo matching task.
Face Spoofing Detection by Fusing Binocular Depth and Spatial Pyramid Coding Micro-Texture Features
The second one is a high-level micro-texture based feature called Spatial Pyramid Coding Micro-Texture (SPMT) feature.
Single Shot Temporal Action Detection
The main drawback of this framework is that the boundaries of action instance proposals have been fixed during the classification step.
CoupleNet: Coupling Global Structure with Local Parts for Object Detection
To fully explore the local and global properties, in this paper, we propose a novel fully convolutional network, named as CoupleNet, to couple the global structure with local parts for object detection.
Ranked #4 on
Object Detection
on PASCAL VOC 2007
Joint Background Reconstruction and Foreground Segmentation via A Two-stage Convolutional Neural Network
In the first stage, a convolutional encoder-decoder sub-network is employed to reconstruct the background images and encode rich prior knowledge of background scenes.
Temporal Convolution Based Action Proposal: Submission to ActivityNet 2017
Our approach achieves the state-of-the-art performances on both temporal action proposal task and temporal action localization task.
Ranked #10 on
Temporal Action Proposal Generation
on ActivityNet-1.3
