Search Results for author: Yong liu

Found 155 papers, 41 papers with code

Lightweight Object-level Topological Semantic Mapping and Long-term Global Localization based on Graph Matching

no code implementations16 Jan 2022 Fan Wang, Chaofan Zhang, Fulin Tang, Hongkui Jiang, Yihong Wu, Yong liu

In this paper, we present a novel lightweight object-level mapping and localization method with high accuracy and robustness.

Graph Matching

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

no code implementations12 Jan 2022 Jiangning Zhang, Chao Xu, Jian Li, Yue Han, Yabiao Wang, Ying Tai, Yong liu

In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-sampling operation for the target device.

Colorization Super-Resolution

Deep Domain Adversarial Adaptation for Photon-efficient Imaging Based on Spatiotemporal Inception Network

1 code implementation7 Jan 2022 YiWei Chen, Gongxin Yao, Yong liu, Yu Pan

In single-photon LiDAR, photon-efficient imaging captures the 3D structure of a scene by only several detected signal photons per pixel.

Domain Adaptation

Robust photon-efficient imaging using a pixel-wise residual shrinkage network

1 code implementation5 Jan 2022 Gongxin Yao, YiWei Chen, Yong liu, Xiaomin Hu, Yu Pan

Single-photon light detection and ranging (LiDAR) has been widely applied to 3D imaging in challenging scenarios.

Depth Estimation

Dynamically Stable Poincaré Embeddings for Neural Manifolds

no code implementations21 Dec 2021 Jun Chen, Yuang Liu, Xiangrui Zhao, Yong liu

As a result, we prove that, if initial metrics have an $L^2$-norm perturbation which deviates from the Hyperbolic metric on the Poincar\'e ball, the scaled Ricci-DeTurck flow of such metrics smoothly and exponentially converges to the Hyperbolic metric.

Image Classification

SelFSR: Self-Conditioned Face Super-Resolution in the Wild via Flow Field Degradation Network

no code implementations20 Dec 2021 Xianfang Zeng, Jiangning Zhang, Liang Liu, Guangzhong Tian, Yong liu

To tackle this problem, we propose a novel domain-adaptive degradation network for face super-resolution in the wild.


Searching Parameterized AP Loss for Object Detection

1 code implementation NeurIPS 2021 Chenxin Tao, Zizhang Li, Xizhou Zhu, Gao Huang, Yong liu, Jifeng Dai

In this paper, we propose Parameterized AP Loss, where parameterized functions are introduced to substitute the non-differentiable components in the AP calculation.

Object Detection

MSP : Refine Boundary Segmentation via Multiscale Superpixel

no code implementations3 Dec 2021 Jie Zhu, Huabin Huang, Banghuai Li, Yong liu, Leye Wang

Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the information passing within feature map.

Scene Parsing Semantic Segmentation

Towards Sharper Generalization Bounds for Structured Prediction

no code implementations NeurIPS 2021 Shaojie Li, Yong liu

In the smoothness scenario, we provide generalization bounds that are not only a logarithmic dependency on the label set cardinality but a faster convergence rate of order $\mathcal{O}(\frac{1}{n})$ on the sample size $n$.

Generalization Bounds Structured Prediction

Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation

no code implementations NeurIPS 2021 Shaogao Lv, Junhui Wang, Jiankun Liu, Yong liu

In this paper, we provide theoretical results of estimation bounds and excess risk upper bounds for support vector machine (SVM) with sparse multi-kernel representation.

Refined Learning Bounds for Kernel and Approximate $k$-Means

no code implementations NeurIPS 2021 Yong liu

In this paper, we study the statistical properties of kernel $k$-means and Nystr\"{o}m-based kernel $k$-means, and obtain optimal clustering risk bounds, which improve the existing risk bounds.

Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN

no code implementations25 Nov 2021 Wen Yu, Baiying Lei, Yanyan Shen, Shuqiang Wang, Yong liu, Zhiguang Feng, Yong Hu, Michael K. Ng

In this work, a novel Multidirectional Perception Generative Adversarial Network (MP-GAN) is proposed to visualize the morphological features indicating the severity of AD for patients of different stages.

MaIL: A Unified Mask-Image-Language Trimodal Network for Referring Image Segmentation

no code implementations21 Nov 2021 Zizhang Li, Mengmeng Wang, Jianbiao Mei, Yong liu

Referring image segmentation is a typical multi-modal task, which aims at generating a binary mask for referent described in given language expressions.

Referring Expression Segmentation Semantic Segmentation

Green CWS: Extreme Distillation and Efficient Decode Method Towards Industrial Application

no code implementations17 Nov 2021 Yulan Hu, Yong liu

Benefiting from the strong ability of the pre-trained model, the research on Chinese Word Segmentation (CWS) has made great progress in recent years.

Chinese Word Segmentation Language Modelling

Thoughts on the Consistency between Ricci Flow and Neural Network Behavior

no code implementations16 Nov 2021 Jun Chen, Tianxin Huang, Wenzhou Chen, Yong liu

The Ricci flow is a partial differential equation for evolving the metric in a Riemannian manifold to make it more regular.

A layer-stress learning framework universally augments deep neural network tasks

no code implementations14 Nov 2021 Shihao Shao, Yong liu, Qinghua Cui

Here we presented a layer-stress deep learning framework (x-NN) which implemented automatic and wise depth decision on shallow or deep feature map in a deep network through firstly designing enough number of layers and then trading off them by Multi-Head Attention Block.

Learning Rates for Nonconvex Pairwise Learning

no code implementations9 Nov 2021 Shaojie Li, Yong liu

We first successfully establish learning rates for these algorithms in a general nonconvex setting, where the analysis sheds insights on the trade-off between optimization and generalization and the role of early-stopping.

Metric Learning

Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking

no code implementations28 Oct 2021 Mengmeng Wang, Xiaoqian Yang, Yong liu

Visual object tracking performance has been dramatically improved in recent years, but some severe challenges remain open, like distractors and occlusions.

Contrastive Learning Visual Object Tracking +1

Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs

1 code implementation20 Oct 2021 Kaichao You, Yong liu, Jianmin Wang, Michael I. Jordan, Mingsheng Long

In this paper, we propose a new paradigm of exploiting model hubs by ranking and tuning pre-trained models: (1) Our conference work~\citep{you_logme:_2021} proposed LogME to estimate the maximum value of label evidence given features extracted by pre-trained models, which can rank all the PTMs in a model hub for various types of PTMs and tasks \emph{before fine-tuning}.

Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation

no code implementations20 Oct 2021 Yidan Hu, Yong liu, Chunyan Miao, Gongqi Lin, Yuan Miao

In this paper, we propose a novel explanation generation framework, named Hierarchical Aspect-guided explanation Generation (HAG), for explainable recommendation.

Recommendation Systems

A Prior Guided Adversarial Representation Learning and Hypergraph Perceptual Network for Predicting Abnormal Connections of Alzheimer's Disease

no code implementations12 Oct 2021 Qiankun Zuo, Baiying Lei, Shuqiang Wang, Yong liu, BingChuan Wang, Yanyan Shen

The proposed model can evaluate characteristics of abnormal brain connections at different stages of Alzheimer's disease, which is helpful for cognitive disease study and early treatment.

Representation Learning

DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's disease

no code implementations12 Oct 2021 Junren Pan, Baiying Lei, Shuqiang Wang, BingChuan Wang, Yong liu, Yanyan Shen

In this work, a novel decoupling generative adversarial network (DecGAN) is proposed to detect abnormal neural circuits for AD.

Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences

1 code implementation1 Oct 2021 Meng Liu, Yong liu

Therefore, we propose a new inductive network representation learning method called MNCI by mining neighborhood and community influences in temporal networks.

Link Prediction Node Classification +1

Geometry-Entangled Visual Semantic Transformer for Image Captioning

no code implementations29 Sep 2021 Ling Cheng, Wei Wei, Feida Zhu, Yong liu, Chunyan Miao

However, those fusion-based models, they are still criticized for the lack of geometry information for inter and intra attention refinement.

Image Captioning

Mask and Understand: Evaluating the Importance of Parameters

no code implementations29 Sep 2021 Bowei Zhu, Yong liu

Influence functions are classic techniques from robust statistics based on first-order Taylor approximations that have been widely used in the machine learning community to estimate small perturbations of datasets accurately to the model.

Feature Importance

Sharpness-Aware Minimization in Large-Batch Training: Training Vision Transformer In Minutes

no code implementations29 Sep 2021 Yong liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You

Large-batch training is an important direction for distributed machine learning, which can improve the utilization of large-scale clusters and therefore accelerate the training process.

Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

1 code implementation23 Sep 2021 Xuemeng Yang, Hao Zou, Xin Kong, Tianxin Huang, Yong liu, Wanlong Li, Feng Wen, Hongbo Zhang

Specifically, the network takes a raw point cloud as input, and merges the features from the segmentation branch into the completion branch hierarchically to provide semantic information.

3D Semantic Segmentation Autonomous Driving +1

A Survey on Reinforcement Learning for Recommender Systems

no code implementations22 Sep 2021 Yuanguo Lin, Yong liu, Fan Lin, Pengcheng Wu, Wenhua Zeng, Chunyan Miao

Recommender systems have been widely applied in different real-life scenarios to help us find useful information.

Recommendation Systems

ActionCLIP: A New Paradigm for Video Action Recognition

1 code implementation17 Sep 2021 Mengmeng Wang, Jiazheng Xing, Yong liu

Moreover, to handle the deficiency of label texts and make use of tremendous web data, we propose a new paradigm based on this multimodal learning framework for action recognition, which we dub "pre-train, prompt and fine-tune".

Action Classification Action Recognition +3

Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

2 code implementations ICCV 2021 Lina Liu, Xibin Song, Mengmeng Wang, Yong liu, Liangjun Zhang

Meanwhile, to guarantee that the day and night images contain the same information, the domain-separated network takes the day-time images and corresponding night-time images (generated by GAN) as input, and the private and invariant feature extractors are learned by orthogonality and similarity loss, where the domain gap can be alleviated, thus better depth maps can be expected.

Monocular Depth Estimation

Go Wider Instead of Deeper

no code implementations25 Jul 2021 Fuzhao Xue, Ziji Shi, Futao Wei, Yuxuan Lou, Yong liu, Yang You

To achieve better performance with fewer trainable parameters, recent methods are proposed to go shallower by parameter sharing or model compressing along with the depth.

Image Classification

3D Brain Reconstruction by Hierarchical Shape-Perception Network from a Single Incomplete Image

no code implementations23 Jul 2021 Bowen Hu, Baiying Lei, Shuqiang Wang, Yong liu, BingChuan Wang, Min Gan, Yanyan Shen

A branching predictor and several hierarchical attention pipelines are constructed to generate point clouds that accurately describe the incomplete images and then complete these point clouds with high quality.

3D Shape Reconstruction

Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction

no code implementations21 Jul 2021 Qiankun Zuo, Baiying Lei, Yanyan Shen, Yong liu, Zhiguang Feng, Shuqiang Wang

Then two hypergraphs are constructed from the latent representations and the adversarial network based on graph convolution is employed to narrow the distribution difference of hyperedge features.

alzheimer's disease detection Disease Prediction +1

Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis

no code implementations21 Jul 2021 Junren Pan, Baiying Lei, Yanyan Shen, Yong liu, Zhiguang Feng, Shuqiang Wang

Using multimodal neuroimaging data to characterize brain network is currently an advanced technique for Alzheimer's disease(AD) Analysis.

White Matter Fiber Tractography

A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction

no code implementations21 Jul 2021 Bowen Hu, Baiying Lei, Yanyan Shen, Yong liu, Shuqiang Wang

Fusing medical images and the corresponding 3D shape representation can provide complementary information and microstructure details to improve the operational performance and accuracy in brain surgery.

3D Shape Representation

Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints

no code implementations19 Jul 2021 Shaojie Li, Yong liu

the sample size $n$ for ERM and SGD with milder assumptions in convex learning and similar high probability rates of order $\mathcal{O} (1/n)$ in nonconvex learning, rather than in expectation.

Learning Theory Stochastic Optimization

Few-Shot Domain Adaptation with Polymorphic Transformers

1 code implementation10 Jul 2021 Shaohua Li, Xiuchao Sui, Jie Fu, Huazhu Fu, Xiangde Luo, Yangqin Feng, Xinxing Xu, Yong liu, Daniel Ting, Rick Siow Mong Goh

Thus, the chance of overfitting the annotations is greatly reduced, and the model can perform robustly on the target domain after being trained on a few annotated images.

Domain Adaptation

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

1 code implementation7 Jul 2021 Xin Zhou, Aixin Sun, Yong liu, Jie Zhang, Chunyan Miao

Further, negative items should be carefully sampled under the defined distribution, in order to avoid selecting an observed positive item in the training dataset.

Collaborative Filtering Self-Supervised Learning

SSC: Semantic Scan Context for Large-Scale Place Recognition

1 code implementation1 Jul 2021 Lin Li, Xin Kong, Xiangrui Zhao, Tianxin Huang, Yong liu

We also present a two-step global semantic ICP to obtain the 3D pose (x, y, yaw) used to align the point cloud to improve matching performance.

Translation Visual Place Recognition

SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure

no code implementations22 Jun 2021 Lin Li, Xin Kong, Xiangrui Zhao, Wanlong Li, Feng Wen, Hongbo Zhang, Yong liu

LiDAR-based SLAM system is admittedly more accurate and stable than others, while its loop closure detection is still an open issue.

3D Semantic Segmentation Loop Closure Detection

Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems

no code implementations9 Jun 2021 Yinan Zhang, Boyang Li, Yong liu, Hao Wang, Chunyan Miao

In this work, we propose a new initialization scheme for user and item embeddings called Laplacian Eigenmaps with Popularity-based Regularization for Isolated Data (LEPORID).

Recommendation Systems

TransVOS: Video Object Segmentation with Transformers

1 code implementation1 Jun 2021 Jianbiao Mei, Mengmeng Wang, Yeneng Lin, Yi Yuan, Yong liu

Recently, Space-Time Memory Network (STM) based methods have achieved state-of-the-art performance in semi-supervised video object segmentation (VOS).

One-shot visual object segmentation Semantic Segmentation +1

Concurrent Adversarial Learning for Large-Batch Training

no code implementations1 Jun 2021 Yong liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You

Current methods usually use extensive data augmentation to increase the batch size, but we found the performance gain with data augmentation decreases as batch size increases, and data augmentation will become insufficient after certain point.

Data Augmentation

Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model

1 code implementation NeurIPS 2021 Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong liu

Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them have consistent mathematical representation.

Image Retrieval

CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation

1 code implementation Findings (ACL) 2021 Chujie Zheng, Yong liu, Wei Chen, Yongcai Leng, Minlie Huang

However, existing methods for empathetic response generation usually either consider only one empathy factor or ignore the hierarchical relationships between different factors, leading to a weak ability of empathy modeling.

Empathetic Response Generation Open-Domain Dialog

KECRS: Towards Knowledge-Enriched Conversational Recommendation System

no code implementations18 May 2021 Tong Zhang, Yong liu, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions.

Entity Embeddings Knowledge Graphs +2

Towards Sharper Utility Bounds for Differentially Private Pairwise Learning

no code implementations7 May 2021 Yilin Kang, Yong liu, Jian Li, Weiping Wang

Pairwise learning focuses on learning tasks with pairwise loss functions, depends on pairs of training instances, and naturally fits for modeling relationships between pairs of samples.

DeepMI: Deep Multi-lead ECG Fusion for Identifying Myocardial Infarction and its Occurrence-time

no code implementations31 Mar 2021 Girmaw Abebe Tadesse, Hamza Javed, Yong liu, Jin Liu, Jiyan Chen, Komminist Weldemariam, Tingting Zhu

We propose an end-to-end deep learning approach, DeepMI, to classify MI from normal cases as well as identifying the time-occurrence of MI (defined as acute, recent and old), using a collection of fusion strategies on 12 ECG leads at data-, feature-, and decision-level.

Transfer Learning

LogME: Practical Assessment of Pre-trained Models for Transfer Learning

1 code implementation22 Feb 2021 Kaichao You, Yong liu, Jianmin Wang, Mingsheng Long

In pursuit of a practical assessment method, we propose to estimate the maximum value of label evidence given features extracted by pre-trained models.

Model Selection Transfer Learning

Large topological Hall effect near room temperature in noncollinear ferromagnet LaMn2Ge2 single crystal

no code implementations11 Feb 2021 Gaoshang Gong, Longmeng Xu, Yuming Bai, Yongqiang Wang, Songliu Yuan, Yong liu, Zhaoming Tian

Non-trivial spin structures in itinerant magnets can give rise to topological Hall effect (THE) due to the interacting local magnetic moments and conductive electrons.

Strongly Correlated Electrons

One-shot Face Reenactment Using Appearance Adaptive Normalization

no code implementations8 Feb 2021 Guangming Yao, Yi Yuan, Tianjia Shao, Shuang Li, Shanqi Liu, Yong liu, Mengmeng Wang, Kun Zhou

The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a driving image) while keeping its original appearance.

Face Reenactment

Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation

no code implementations5 Feb 2021 Jilin Tang, Yi Yuan, Tianjia Shao, Yong liu, Mengmeng Wang, Kun Zhou

In this paper we tackle the problem of pose guided person image generation, which aims to transfer a person image from the source pose to a novel target pose while maintaining the source appearance.

Image Generation

Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity with Ensemble Learning

no code implementations14 Jan 2021 Tongyu Zong, Chen Li, Yuanyuan Lei, Guangyu Li, Houwei Cao, Yong liu

In this paper, we propose Cocktail Edge Caching, that tackles the dynamic popularity and heterogeneity through ensemble learning.

Ensemble Learning Time Series +1

Effective Distributed Learning with Random Features: Improved Bounds and Algorithms

no code implementations ICLR 2021 Yong liu, Jiankun Liu, Shuqiang Wang

In this paper, we study the statistical properties of distributed kernel ridge regression together with random features (DKRR-RF), and obtain optimal generalization bounds under the basic setting, which can substantially relax the restriction on the number of local machines in the existing state-of-art bounds.

Generalization Bounds

RFNet: Recurrent Forward Network for Dense Point Cloud Completion

no code implementations ICCV 2021 Tianxin Huang, Hao Zou, Jinhao Cui, Xuemeng Yang, Mengmeng Wang, Xiangrui Zhao, Jiangning Zhang, Yi Yuan, Yifan Xu, Yong liu

The RFE extracts multiple global features from the incomplete point clouds for different recurrent levels, and the FDC generates point clouds in a coarse-to-fine pipeline.

Point Cloud Completion

Fast Estimation for Privacy and Utility in Differentially Private Machine Learning

no code implementations1 Jan 2021 Yuzhe Li, Yong liu, Weipinng Wang, Bo Li, Nan Liu

In this paper, we deduce the influence of $\epsilon$ on utility private learning models through strict mathematical derivation, and propose a novel approximate approach for estimating the utility of any $\epsilon$ value.

Optimizing Quantized Neural Networks with Natural Gradient

no code implementations1 Jan 2021 Jun Chen, Hanwen Chen, Jiangning Zhang, Wenzhou Chen, Yong liu, Yunliang Jiang

Quantized Neural Networks (QNNs) have achieved an enormous step in improving computational efficiency, making it possible to deploy large models to mobile and miniaturized devices.

A Hybrid Bandit Framework for Diversified Recommendation

no code implementations24 Dec 2020 Qinxu Ding, Yong liu, Chunyan Miao, Fei Cheng, Haihong Tang

Previous interactive recommendation methods primarily focus on learning users' personalized preferences on the relevance properties of an item set.

Recommendation Systems

CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth

no code implementations18 Dec 2020 Xingxing Zuo, Nathaniel Merrill, Wei Li, Yong liu, Marc Pollefeys, Guoquan Huang

In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth maps of the immediate surroundings.

Depth Estimation Pose Estimation

Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation

no code implementations16 Dec 2020 Hao Tang, Xingwei Liu, Kun Han, Shanlin Sun, Narisu Bai, Xuming Chen, Huang Qian, Yong liu, Xiaohui Xie

State-of-the-art CNN segmentation models apply either 2D or 3D convolutions on input images, with pros and cons associated with each method: 2D convolution is fast, less memory-intensive but inadequate for extracting 3D contextual information from volumetric images, while the opposite is true for 3D convolution.

Semantic Segmentation

Keyword-Guided Neural Conversational Model

no code implementations15 Dec 2020 Peixiang Zhong, Yong liu, Hao Wang, Chunyan Miao

We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smoothly and fast.

Knowledge Graphs Word Embeddings

FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion

no code implementations15 Dec 2020 Lina Liu, Xibin Song, Xiaoyang Lyu, Junwei Diao, Mengmeng Wang, Yong liu, Liangjun Zhang

Then, a refined depth map is further obtained using a residual learning strategy in the coarse-to-fine stage with a coarse depth map and color image as input.

Depth Completion

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

1 code implementation14 Dec 2020 Xiaoyang Lyu, Liang Liu, Mengmeng Wang, Xin Kong, Lina Liu, Yong liu, Xinxin Chen, Yi Yuan

To obtainmore accurate depth estimation in large gradient regions, itis necessary to obtain high-resolution features with spatialand semantic information.

Monocular Depth Estimation Self-Supervised Learning

FlowMOT: 3D Multi-Object Tracking by Scene Flow Association

no code implementations14 Dec 2020 Guangyao Zhai, Xin Kong, Jinhao Cui, Yong liu, Zhen Yang

Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability.

3D Multi-Object Tracking motion prediction +1

DLPAlign: A Deep Learning based Progressive Alignment Method for Multiple Protein Sequences

1 code implementation21 Nov 2020 Mengmeng Kuang, Yong liu, Lufei Gao

This paper proposed a novel and straightforward approach to improve the accuracy of progressive multiple protein sequence alignment method.

Decision Making Multiple Sequence Alignment +1

Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain

no code implementations9 Nov 2020 Senrong You, Yong liu, Baiying Lei, Shuqiang Wang

Specifically, FP-GANs firstly divides an MR image into low-frequency global approximation and high-frequency anatomical texture in wavelet domain.

Image Super-Resolution

HILONet: Hierarchical Imitation Learning from Non-Aligned Observations

no code implementations5 Nov 2020 Shanqi Liu, Junjie Cao, Wenzhou Chen, Licheng Wen, Yong liu

In this work, we propose a new imitation learning approach called Hierarchical Imitation Learning from Observation(HILONet), which adopts a hierarchical structure to choose feasible sub-goals from demonstrated observations dynamically.

Imitation Learning

CL-MAPF: Multi-Agent Path Finding for Car-Like Robots with Kinematic and Spatiotemporal Constraints

1 code implementation1 Nov 2020 Licheng Wen, Zhen Zhang, Zhe Chen, Xiangrui Zhao, Yong liu

In this paper, we give a mathematical formalization of Multi-Agent Path Finding for Car-Like robots (CL-MAPF) problem.

Robotics Multiagent Systems

APB2FaceV2: Real-Time Audio-Guided Multi-Face Reenactment

1 code implementation25 Oct 2020 Jiangning Zhang, Xianfang Zeng, Chao Xu, Jun Chen, Yong liu, Yunliang Jiang

Audio-guided face reenactment aims to generate a photorealistic face that has matched facial expression with the input audio.

Face Reenactment

F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking

no code implementations22 Oct 2020 Hao Zou, Jinhao Cui, Xin Kong, Chujuan Zhang, Yong liu, Feng Wen, Wanlong Li

A main challenge in 3D single object tracking is how to reduce search space for generating appropriate 3D candidates.

Object Tracking

Semantic Graph Based Place Recognition for 3D Point Clouds

1 code implementation26 Aug 2020 Xin Kong, Xuemeng Yang, Guangyao Zhai, Xiangrui Zhao, Xianfang Zeng, Mengmeng Wang, Yong liu, Wanlong Li, Feng Wen

First, we propose a novel semantic graph representation for the point cloud scenes by reserving the semantic and topological information of the raw point cloud.

Graph Matching Graph Similarity

LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking

no code implementations17 Aug 2020 Xingxing Zuo, Yulin Yang, Patrick Geneva, Jiajun Lv, Yong liu, Guoquan Huang, Marc Pollefeys

Only the tracked planar points belonging to the same plane will be used for plane initialization, which makes the plane extraction efficient and robust.


Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation

2 code implementations29 Jul 2020 Jiajun Lv, Jinhong Xu, Kewei Hu, Yong liu, Xingxing Zuo

Sensor calibration is the fundamental block for a multi-sensor fusion system.


Dive Deeper Into Box for Object Detection

no code implementations ECCV 2020 Ran Chen, Yong liu, Mengdan Zhang, Shu Liu, Bei Yu, Yu-Wing Tai

Anchor free methods have defined the new frontier in state-of-the-art object detection researches where accurate bounding box estimation is the key to the success of these methods.

Object Detection

Neural Architecture Optimization with Graph VAE

no code implementations18 Jun 2020 Jian Li, Yong liu, Jiankun Liu, Weiping Wang

The encoder and the decoder belong to a graph VAE, mapping architectures between continuous representations and network architectures.

Neural Architecture Search

Collision-free Trajectory Planning for Autonomous Surface Vehicle

no code implementations20 May 2020 Licheng Wen, Jiaqing Yan, Xuemeng Yang, Yong liu, Yong Gu

We apply a numerical optimization method in the back-end to generate the trajectory.


Hierarchical and Efficient Learning for Person Re-Identification

no code implementations18 May 2020 Jiangning Zhang, Liang Liu, Chao Xu, Yong liu

Recent works in the person re-identification task mainly focus on the model accuracy while ignore factors related to the efficiency, e. g. model size and latency, which are critical for practical application.

Person Re-Identification

APB2Face: Audio-guided face reenactment with auxiliary pose and blink signals

1 code implementation30 Apr 2020 Jiangning Zhang, Liang Liu, Zhu-Cun Xue, Yong liu

Audio-guided face reenactment aims at generating photorealistic faces using audio information while maintaining the same facial movement as when speaking to a real person.

Face Reenactment

Towards Persona-Based Empathetic Conversational Models

1 code implementation EMNLP 2020 Peixiang Zhong, Chen Zhang, Hao Wang, Yong liu, Chunyan Miao

To this end, we propose a new task towards persona-based empathetic conversations and present the first empirical study on the impact of persona on empathetic responding.

Learning Hierarchical Review Graph Representations for Recommendation

no code implementations24 Apr 2020 Yong liu, Susen Yang, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang

Therefore, they may not be effective in capturing the global dependency between words, and tend to be easily biased by noise review information.

Graph Attention

Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

no code implementations24 Apr 2020 Susen Yang, Yong liu, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang

Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation.

Graph Attention

Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations

1 code implementation12 Apr 2020 Shaohua Li, Xiuchao Sui, Jie Fu, Yong liu, Rick Siow Mong Goh

To make CNNs more invariant to transformations, we propose "Feature Lenses", a set of ad-hoc modules that can be easily plugged into a trained model (referred to as the "host model").

A Learning Framework for n-bit Quantized Neural Networks toward FPGAs

1 code implementation6 Apr 2020 Jun Chen, Liang Liu, Yong liu, Xianfang Zeng

Furthermore, we also design a shift vector processing element (SVPE) array to replace all 16-bit multiplications with SHIFT operations in convolution operation on FPGAs.

Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose

no code implementations29 Mar 2020 Xianfang Zeng, Yusu Pan, Mengmeng Wang, Jiangning Zhang, Yong liu

On the one hand, we adopt the deforming autoencoder to disentangle identity and pose representations.

Face Reenactment

Extended Feature Pyramid Network for Small Object Detection

2 code implementations16 Mar 2020 Chunfang Deng, Mengmeng Wang, Liang Liu, Yong liu

Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.

Small Object Detection

Nearly Optimal Clustering Risk Bounds for Kernel K-Means

no code implementations9 Mar 2020 Yong Liu, Lizhong Ding, Weiping Wang

In this paper, we study the statistical properties of kernel $k$-means and obtain a nearly optimal excess clustering risk bound, substantially improving the state-of-art bounds in the existing clustering risk analyses.

Theoretical Analysis of Divide-and-Conquer ERM: Beyond Square Loss and RKHS

no code implementations9 Mar 2020 Yong Liu, Lizhong Ding, Weiping Wang

However, the studies on learning theory for general loss functions and hypothesis spaces remain limited.

Learning Theory

Propagating Asymptotic-Estimated Gradients for Low Bitwidth Quantized Neural Networks

no code implementations4 Mar 2020 Jun Chen, Yong liu, Hao Zhang, Shengnan Hou, Jian Yang

Meanwhile, we propose a M-bit Inputs and N-bit Weights Network (MINW-Net) trained by AQE, a quantized neural network with 1-3 bits weights and activations.

Convolutional Spectral Kernel Learning

no code implementations28 Feb 2020 Jian Li, Yong liu, Weiping Wang

Recently, non-stationary spectral kernels have drawn much attention, owing to its powerful feature representation ability in revealing long-range correlations and input-dependent characteristics.

Input Perturbation: A New Paradigm between Central and Local Differential Privacy

1 code implementation20 Feb 2020 Yilin Kang, Yong liu, Ben Niu, Xin-Yi Tong, Likun Zhang, Weiping Wang

By adding noise to the original training data and training with the `perturbed data', we achieve ($\epsilon$,$\delta$)-differential privacy on the final model, along with some kind of privacy on the original data.

Differentially Private ERM Based on Data Perturbation

no code implementations20 Feb 2020 Yilin Kang, Yong liu, Lizhong Ding, Xinwang Liu, Xin-Yi Tong, Weiping Wang

In this paper, after observing that different training data instances affect the machine learning model to different extents, we attempt to improve the performance of differentially private empirical risk minimization (DP-ERM) from a new perspective.

Variational Quantum Circuits for Quantum State Tomography

1 code implementation16 Dec 2019 Yong Liu, Dongyang Wang, Shichuan Xue, Anqi Huang, Xiang Fu, Xiaogang Qiang, Ping Xu, He-Liang Huang, Mingtang Deng, Chu Guo, Xuejun Yang, Junjie Wu

We demonstrate our method by performing numerical simulations for the tomography of the ground state of a one-dimensional quantum spin chain, using a variational quantum circuit simulator.

Quantum State Tomography

Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning

no code implementations11 Dec 2019 Tianying Wang, Hao Zhang, Wei Qi Toh, Hongyuan Zhu, Cheston Tan, Yan Wu, Yong liu, Wei Jing

The proposed method is able to efficiently generalize the previously learned task by model fusion to solve the environment adaptation problem.

RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization

no code implementations11 Dec 2019 Tianying Wang, Wei Qi Toh, Hao Zhang, Xiuchao Sui, Shaohua Li, Yong liu, Wei Jing

The proposed RoboCoDraw system takes a real human face image as input, converts it to a stylized avatar, then draws it with a robotic arm.

Robotics Graphics

Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test

no code implementations NeurIPS 2019 Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong liu, Yu Li, Ling Shao

DEAN can be interpreted as a GOF game between two generative networks, where one explicit generative network learns an energy-based distribution that fits the real data, and the other implicit generative network is trained by minimizing a GOF test statistic between the energy-based distribution and the generated data, such that the underlying distribution of the generated data is close to the energy-based distribution.

Multi-Agent Game Abstraction via Graph Attention Neural Network

no code implementations25 Nov 2019 Yong Liu, Weixun Wang, Yujing Hu, Jianye Hao, Xingguo Chen, Yang Gao

Traditional methods attempt to use pre-defined rules to capture the interaction relationship between agents.

Graph Attention Multi-agent Reinforcement Learning

Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints

no code implementations13 Nov 2019 Xingxing Zuo, Mingming Zhang, Yiming Chen, Yong liu, Guoquan Huang, Mingyang Li

While visual localization or SLAM has witnessed great progress in past decades, when deploying it on a mobile robot in practice, few works have explicitly considered the kinematic (or dynamic) constraints of the real robotic system when designing state estimators.

Visual Localization

Weighted Distributed Differential Privacy ERM: Convex and Non-convex

no code implementations23 Oct 2019 Yilin Kang, Yong liu, Weiping Wang

By detailed theoretical analysis, we show that in distributed setting, the noise bound and the excess empirical risk bound can be improved by considering different weights held by multiple parties.

Automatic Data Augmentation by Learning the Deterministic Policy

1 code implementation18 Oct 2019 Yinghuan Shi, Tiexin Qin, Yong liu, Jiwen Lu, Yang Gao, Dinggang Shen

By introducing an unified optimization goal, DeepAugNet intends to combine the data augmentation and the deep model training in an end-to-end training manner which is realized by simultaneously training a hybrid architecture of dueling deep Q-learning algorithm and a surrogate deep model.

Data Augmentation Q-Learning

Semi-supervised Vector-valued Learning: From Theory to Algorithm

1 code implementation11 Sep 2019 Jian Li, Yong liu, Weiping Wang

Vector-valued learning, where the output space admits a vector-valued structure, is an important problem that covers a broad family of important domains, e. g. multi-label learning and multi-class classification.

Multi-class Classification Multi-Label Learning

Automated Spectral Kernel Learning

1 code implementation11 Sep 2019 Jian Li, Yong liu, Weiping Wang

The generalization performance of kernel methods is largely determined by the kernel, but common kernels are stationary thus input-independent and output-independent, that limits their applications on complicated tasks.

LIC-Fusion: LiDAR-Inertial-Camera Odometry

no code implementations9 Sep 2019 Xingxing Zuo, Patrick Geneva, Woosik Lee, Yong liu, Guoquan Huang

This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points.


Pose Estimation for Ground Robots: On Manifold Representation, Integration, Re-Parameterization, and Optimization

no code implementations8 Sep 2019 Mingming Zhang, Xingxing Zuo, Yiming Chen, Yong liu, Mingyang Li

In this paper, we focus on motion estimation dedicated for non-holonomic ground robots, by probabilistically fusing measurements from the wheel odometer and exteroceptive sensors.

6D Pose Estimation Motion Estimation

From Few to More: Large-scale Dynamic Multiagent Curriculum Learning

no code implementations6 Sep 2019 Weixun Wang, Tianpei Yang, Yong liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao

In this paper, we design a novel Dynamic Multiagent Curriculum Learning (DyMA-CL) to solve large-scale problems by starting from learning on a multiagent scenario with a small size and progressively increasing the number of agents.

Face-to-Parameter Translation for Game Character Auto-Creation

no code implementations ICCV 2019 Tianyang Shi, Yi Yuan, Changjie Fan, Zhengxia Zou, Zhenwei Shi, Yong liu

Character customization system is an important component in Role-Playing Games (RPGs), where players are allowed to edit the facial appearance of their in-game characters with their own preferences rather than using default templates.

Style Transfer Translation

PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation

1 code implementation IJCAI 2019 Qiong Wu, Yong liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan

This paper proposes Personalized Diversity-promoting GAN (PD-GAN), a novel recommendation model to generate diverse, yet relevant recommendations.

Recommendation Systems

Multi-Instance Multi-Scale CNN for Medical Image Classification

no code implementations4 Jul 2019 Shaohua Li, Yong liu, Xiuchao Sui, Cheng Chen, Gabriel Tjio, Daniel Shu Wei Ting, Rick Siow Mong Goh

Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs) are relatively small with unclear boundaries in the whole medical images, and may appear in arbitrary positions across the x, y (and also z in 3D images) dimensions.

General Classification Image Classification +1

Bandit Learning for Diversified Interactive Recommendation

no code implementations1 Jul 2019 Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

Interactive recommender systems that enable the interactions between users and the recommender system have attracted increasing research attentions.

Bayesian Inference Recommendation Systems

PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning

no code implementations19 Jun 2019 Guangyao Zhai, Liang Liu, Linjian Zhang, Yong liu

The feature-encoding module encodes the short-term motion feature in an image pair, while the memory-propagating module captures the long-term motion feature in the consecutive image pairs.

Camera Calibration Motion Estimation +2

Distributed Learning with Random Features

1 code implementation7 Jun 2019 Jian Li, Yong liu, Weiping Wang

Distributed learning and random projections are the most common techniques in large scale nonparametric statistical learning.

Back Attention Knowledge Transfer for Low-Resource Named Entity Recognition

no code implementations4 Jun 2019 Shengfei Lyu, Linghao Sun, Huixiong Yi, Yong liu, Huanhuan Chen, Chunyan Miao

In recent years, great success has been achieved in the field of natural language processing (NLP), thanks in part to the considerable amount of annotated resources.

Low Resource Named Entity Recognition Named Entity Recognition +3

FReeNet: Multi-Identity Face Reenactment

no code implementations CVPR 2020 Jiangning Zhang, Xianfang Zeng, Mengmeng Wang, Yusu Pan, Liang Liu, Yong liu, Yu Ding, Changjie Fan

This paper presents a novel multi-identity face reenactment framework, named FReeNet, to transfer facial expressions from an arbitrary source face to a target face with a shared model.

Face Reenactment

Audio2Face: Generating Speech/Face Animation from Single Audio with Attention-Based Bidirectional LSTM Networks

no code implementations27 May 2019 Guanzhong Tian, Yi Yuan, Yong liu

We propose an end to end deep learning approach for generating real-time facial animation from just audio.

Recent Advances in Diversified Recommendation

no code implementations16 May 2019 Qiong Wu, Yong liu, Chunyan Miao, Yin Zhao, Lu Guan, Haihong Tang

With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not.

Recommendation Systems

An Evaluation of Transfer Learning for Classifying Sales Engagement Emails at Large Scale

no code implementations19 Apr 2019 Yong Liu, Pavel Dmitriev, Yifei HUANG, Andrew Brooks, Li Dong

Our results show that fine-tuning of the BERT model outperforms with as few as 300 labeled samples, but underperforms with fewer than 300 labeled samples, relative to all the feature-based approaches using different embeddings.

Language Modelling Transfer Learning

Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation

no code implementations19 Mar 2019 Yong Liu, Yinan Zhang, Qiong Wu, Chunyan Miao, Lizhen Cui, Binqiang Zhao, Yin Zhao, Lu Guan

Interactive recommendation that models the explicit interactions between users and the recommender system has attracted a lot of research attentions in recent years.

Recommendation Systems

Multi-Scale Quasi-RNN for Next Item Recommendation

no code implementations26 Feb 2019 Chaoyue He, Yong liu, Qingyu Guo, Chunyan Miao

To this end, architectural inductive biases such as Markov-Chains, Recurrent models, Convolutional networks and many others have demonstrated reasonable success on this task.

Recommendation Systems

Efficient Cross-Validation for Semi-Supervised Learning

no code implementations13 Feb 2019 Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang

In this paper, we provide a method to approximate the CV for manifold regularization based on a notion of robust statistics, called Bouligand influence function (BIF).

Model Selection

Very Long Term Field of View Prediction for 360-degree Video Streaming

1 code implementation4 Feb 2019 Chenge Li, Weixi Zhang, Yong liu, Yao Wang

In this work, we treat the FoV prediction as a sequence learning problem, and propose to predict the target user's future FoV not only based on the user's own past FoV center trajectory but also other users' future FoV locations.

Max-Diversity Distributed Learning: Theory and Algorithms

no code implementations19 Dec 2018 Yong Liu, Jian Li, Weiping Wang

We study the risk performance of distributed learning for the regularization empirical risk minimization with fast convergence rate, substantially improving the error analysis of the existing divide-and-conquer based distributed learning.

Learning Theory

Dynamic Spatio-temporal Graph-based CNNs for Traffic Prediction

no code implementations5 Dec 2018 Ken Chen, Fei Chen, Baisheng Lai, Zhongming Jin, Yong liu, Kai Li, Long Wei, Pengfei Wang, Yandong Tang, Jianqiang Huang, Xian-Sheng Hua

To capture the graph dynamics, we use the graph prediction stream to predict the dynamic graph structures, and the predicted structures are fed into the flow prediction stream.

Traffic Prediction

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

no code implementations5 Dec 2018 Ying Shen, Joël Colloc, Armelle Jacquet-Andrieu, Ziyi Guo, Yong liu

Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS).

General Classification

Approach for Semi-automatic Construction of Anti-infective Drug Ontology Based on Entity Linking

no code implementations5 Dec 2018 Ying Shen, Yang Deng, Kaiqi Yuan, Li Liu, Yong liu

Experiments show that our selected features have achieved a precision rate of 86. 77%, a recall rate of 89. 03% and an F1 score of 87. 89%.

Entity Linking

A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions

no code implementations5 Dec 2018 Kai Lei, Bing Zhang, Yong liu, Yang Deng, Dongyu Zhang, Ying Shen

In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.

Entity Linking Learning-To-Rank +3

Multi-Class Learning: From Theory to Algorithm

no code implementations NeurIPS 2018 Jian Li, Yong liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang

In this paper, we study the generalization performance of multi-class classification and obtain a shaper data-dependent generalization error bound with fast convergence rate, substantially improving the state-of-art bounds in the existing data-dependent generalization analysis.

General Classification Multi-class Classification

Adaptive Re-ranking of Deep Feature for Person Re-identification

no code implementations21 Nov 2018 Yong Liu, Lin Shang, Andy Song

First, we propose a Deep Feature Fusion (DFF) method to exploit the diverse information embedded in a deep feature.

Person Re-Identification Re-Ranking

SL$^2$MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

no code implementations20 Oct 2018 Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng

Moreover, we also incorporate biological knowledge about genes from protein-protein interaction (PPI) data and Gene Ontology (GO).

AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy

2 code implementations15 Aug 2018 Wentao Zhu, Yufang Huang, Liang Zeng, Xuming Chen, Yong liu, Zhen Qian, Nan Du, Wei Fan, Xiaohui Xie

Methods: Our deep learning model, called AnatomyNet, segments OARs from head and neck CT images in an end-to-end fashion, receiving whole-volume HaN CT images as input and generating masks of all OARs of interest in one shot.

3D Medical Imaging Segmentation

Robust Visual SLAM with Point and Line Features

no code implementations23 Nov 2017 Xingxing Zuo, Xiaojia Xie, Yong liu, Guoquan Huang

In this paper, we develop a robust efficient visual SLAM system that utilizes heterogeneous point and line features.

Stereo Matching Stereo Matching Hand

Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback

no code implementations3 Jul 2017 Peng Yang, Peilin Zhao, Xin Gao, Yong liu

Morever, the proposed algorithm can be scaled up to large-sized datasets after a relaxation.

Large Margin Object Tracking with Circulant Feature Maps

no code implementations CVPR 2017 Mengmeng Wang, Yong liu, Zeyi Huang

Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently.

Object Tracking

Real-time 3D Human Tracking for Mobile Robots with Multisensors

no code implementations15 Mar 2017 Mengmeng Wang, Daobilige Su, Lei Shi, Yong liu, Jaime Valls Miro

An ultrasonic sensor array is employed to provide the range information from the target person to the robot and Gaussian Process Regression is used for partial location estimation (2-D).

Visual Tracking

Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation

4 code implementations17 Oct 2016 Yiyi Liao, Lichao Huang, Yue Wang, Sarath Kodagoda, Yinan Yu, Yong liu

Many standard robotic platforms are equipped with at least a fixed 2D laser range finder and a monocular camera.

Depth Completion

Simple and Efficient Learning using Privileged Information

no code implementations6 Apr 2016 Xinxing Xu, Joey Tianyi Zhou, IvorW. Tsang, Zheng Qin, Rick Siow Mong Goh, Yong liu

The Support Vector Machine using Privileged Information (SVM+) has been proposed to train a classifier to utilize the additional privileged information that is only available in the training phase but not available in the test phase.

Image Categorization

RISAS: A Novel Rotation, Illumination, Scale Invariant Appearance and Shape Feature

no code implementations14 Mar 2016 Kanzhi Wu, Xiaoyang Li, Ravindra Ranasinghe, Gamini Dissanayake, Yong liu

This paper presents a novel appearance and shape feature, RISAS, which is robust to viewpoint, illumination, scale and rotation variations.

Robust Object Tracking with a Hierarchical Ensemble Framework

no code implementations23 Sep 2015 Mengmeng Wang, Yong liu

A discriminative model which accounts for the matching degree of local patches is adopted via a bottom ensemble layer, and a generative model which exploits holistic templates is used to search for the object through the middle ensemble layer as well as an adaptive Kalman filter.

Object Tracking

Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks

no code implementations22 Sep 2015 Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu

As scene images have larger diversity than the iconic object images, it is more challenging for deep learning methods to automatically learn features from scene images with less samples.

General Classification Scene Classification +2

Noise Robust IOA/CAS Speech Separation and Recognition System For The Third 'CHIME' Challenge

no code implementations21 Sep 2015 Xiaofei Wang, Chao Wu, Pengyuan Zhang, Ziteng Wang, Yong liu, Xu Li, Qiang Fu, Yonghong Yan

This paper presents the contribution to the third 'CHiME' speech separation and recognition challenge including both front-end signal processing and back-end speech recognition.

Automatic Speech Recognition Speech Separation

Place classification with a graph regularized deep neural network model

no code implementations12 Jun 2015 Yiyi Liao, Sarath Kodagoda, Yue Wang, Lei Shi, Yong liu

Furthermore, results show that the features automatically learned from the raw input range data can achieve competitive results to the features constructed based on statistical and geometrical information.

General Classification

Image Representation Learning Using Graph Regularized Auto-Encoders

no code implementations3 Dec 2013 Yiyi Liao, Yue Wang, Yong liu

We consider the problem of image representation for the tasks of unsupervised learning and semi-supervised learning.

Image Clustering Representation Learning

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