Search Results for author: Yu Liu

Found 114 papers, 40 papers with code

More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning

1 code implementation ECCV 2020 Yu Liu, Sarah Parisot, Gregory Slabaugh, Xu Jia, Ales Leonardis, Tinne Tuytelaars

Since those regularization strategies are mostly associated with classifier outputs, we propose a MUlti-Classifier (MUC) incremental learning paradigm that integrates an ensemble of auxiliary classifiers to estimate more effective regularization constraints.

Incremental Learning

RelationRS: Relationship Representation Network for Object Detection in Aerial Images

no code implementations13 Oct 2021 Zhiming Liu, Xuefei Zhang, Chongyang Liu, Hao Wang, Chao Sun, Bin Li, Weifeng Sun, Pu Huang, Qingjun Li, Yu Liu, Haipeng Kuang, Jihong Xiu

To address these issues, we propose a relationship representation network for object detection in aerial images (RelationRS): 1) Firstly, multi-scale features are fused and enhanced by a dual relationship module (DRM) with conditional convolution.

Object Detection In Aerial Images

UniNet: Unified Architecture Search with Convolution, Transformer, and MLP

no code implementations8 Oct 2021 Jihao Liu, Hongsheng Li, Guanglu Song, Xin Huang, Yu Liu

Recently, transformer and multi-layer perceptron (MLP) architectures have achieved impressive results on various vision tasks.

Object Detection Semantic Segmentation

Combing Policy Evaluation and Policy Improvement in a Unified f-Divergence Framework

no code implementations24 Sep 2021 Chen Gong, Qiang He, Yunpeng Bai, Xiaoyu Chen, Xinwen Hou, Yu Liu, Guoliang Fan

In this paper, we start from studying the f-divergence between learning policy and sampling policy and derive a novel DRL framework, termed f-Divergence Reinforcement Learning (FRL).

Decision Making

MEPG: A Minimalist Ensemble Policy Gradient Framework for Deep Reinforcement Learning

no code implementations22 Sep 2021 Qiang He, Chen Gong, Yuxun Qu, Xiaoyu Chen, Xinwen Hou, Yu Liu

Ensemble reinforcement learning (RL) aims to mitigate instability in Q-learning and to learn a robust policy, which introduces multiple value and policy functions.


LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders

no code implementations22 Sep 2021 Xiaoyu Chen, Chen Gong, Qiang He, Xinwen Hou, Yu Liu

Variational autoencoders (VAEs), as an important aspect of generative models, have received a lot of research interests and reached many successful applications.

Image Generation

Spatio-temporal Parking Behaviour Forecasting and Analysis Before and During COVID-19

no code implementations15 Aug 2021 Shuhui Gong, Xiaopeng Mo, Rui Cao, Yu Liu, Wei Tu, Ruibin Bai

Parking demand forecasting and behaviour analysis have received increasing attention in recent years because of their critical role in mitigating traffic congestion and understanding travel behaviours.

Epidemiology graph construction +1

Iterative Self-consistent Parallel Magnetic Resonance Imaging Reconstruction based on Nonlocal Low-Rank Regularization

no code implementations10 Aug 2021 Ting Pan, Jizhong Duan, Junfeng Wang, Yu Liu

Recent methods have exploited the nonlocal self-similarity (NSS) of images by imposing nonlocal low-rankness of similar patches to achieve a superior performance.

Unified Regularity Measures for Sample-wise Learning and Generalization

no code implementations9 Aug 2021 Chi Zhang, Xiaoning Ma, Yu Liu, Le Wang, Yuanqi SU, Yuehu Liu

Fundamental machine learning theory shows that different samples contribute unequally both in learning and testing processes.

Learning Theory

Real-time Keypoints Detection for Autonomous Recovery of the Unmanned Ground Vehicle

no code implementations27 Jul 2021 Jie Li, Sheng Zhang, Kai Han, Xia Yuan, Chunxia Zhao, Yu Liu

UGV-KPNet is computationally efficient with a small number of parameters and provides pixel-level accurate keypoints detection results in real-time.

Keypoint Detection

Curvature Graph Neural Network

no code implementations30 Jun 2021 Haifeng Li, Jun Cao, Jiawei Zhu, Yu Liu, Qing Zhu, Guohua Wu

And we propose Curvature Graph Neural Network (CGNN), which effectively improves the adaptive locality ability of GNNs by leveraging the structural property of graph curvature.

Node Classification

Communication Efficient SGD via Gradient Sampling With Bayes Prior

no code implementations CVPR 2021 Liuyihan Song, Kang Zhao, Pan Pan, Yu Liu, Yingya Zhang, Yinghui Xu, Rong Jin

Different from all of them, we regard large and small gradients selection as the exploitation and exploration of gradient information, respectively.

Image Classification Object Detection +1

FNAS: Uncertainty-Aware Fast Neural Architecture Search

no code implementations25 May 2021 Jihao Liu, Ming Zhang, Yangting Sun, Boxiao Liu, Guanglu Song, Yu Liu, Hongsheng Li

Further, an architecture knowledge pool together with a block similarity function is proposed to utilize parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search

A Novel Unified Stereo Stimuli based Binocular Eye-Tracking System for Accurate 3D Gaze Estimation

no code implementations25 Apr 2021 Sunjing Lin, Yu Liu, Shaochu Wang, Chang Li, Han Wang

In this paper, we present a novel noncontact technique for the PoG estimation in a stereoscopic environment, which integrates a 3D stereoscopic display system and an eye-tracking system.

Depth Estimation Eye Tracking +1

Role-Aware Modeling for N-ary Relational Knowledge Bases

1 code implementation20 Apr 2021 Yu Liu, Quanming Yao, Yong Li

N-ary relational knowledge bases (KBs) represent knowledge with binary and beyond-binary relational facts.

Knowledge Graphs

Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval

no code implementations11 Apr 2021 Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

Moreover, feature encoders (as a generator) project uni-modal features into a commonly shared space and attempt to fool the discriminator by maximizing its output information entropy.

Cross-Modal Retrieval

Self-supervised Video Representation Learning by Context and Motion Decoupling

no code implementations CVPR 2021 Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Yinghui Xu, Rong Jin

A key challenge in self-supervised video representation learning is how to effectively capture motion information besides context bias.

Action Recognition motion prediction +2

High-efficiency Euclidean-based Models for Low-dimensional Knowledge Graph Embeddings

no code implementations27 Mar 2021 Kai Wang, Yu Liu, Quan Z. Sheng

Recent knowledge graph embedding (KGE) models based on hyperbolic geometry have shown great potential in a low-dimensional embedding space.

Knowledge Graph Embedding Knowledge Graph Embeddings +1

Lifelong Person Re-Identification via Adaptive Knowledge Accumulation

1 code implementation CVPR 2021 Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

In this work we explore a new and challenging ReID task, namely lifelong person re-identification (LReID), which enables to learn continuously across multiple domains and even generalise on new and unseen domains.

Incremental Learning Person Re-Identification

Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning

no code implementations9 Feb 2021 Yu Liu, Lianghua Huang, Pan Pan, Bin Wang, Yinghui Xu, Rong Jin

However, scaling up the classification task from thousands of semantic labels to millions of instance labels brings specific challenges including 1) the large-scale softmax computation; 2) the slow convergence due to the infrequent visiting of instance samples; and 3) the massive number of negative classes that can be noisy.

Classification General Classification +1

Deep Image Retrieval: A Survey

no code implementations27 Jan 2021 Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew

More specifically, we focus on image retrieval with deep learning and organize the state of the art methods according to the types of deep network structure, deep features, feature enhancement methods, and network fine-tuning strategies.

Content-Based Image Retrieval

Self-supervised Temporal Learning

no code implementations1 Jan 2021 Hao Shao, Yu Liu, Hongsheng Li

Inspired by spatial-based contrastive SSL, we show that significant improvement can be achieved by a proposed temporal-based contrastive learning approach, which includes three novel and efficient modules: temporal augmentations, temporal memory bank and SSTL loss.

Contrastive Learning Self-Supervised Learning +2

Fast MNAS: Uncertainty-aware Neural Architecture Search with Lifelong Learning

no code implementations1 Jan 2021 Jihao Liu, Yangting Sun, Ming Zhang, Boxiao Liu, Yu Liu

Further, a life-long knowledge pool together with a block similarity function is proposed to utilize the lifelong parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search

Switchable K-Class Hyperplanes for Noise-Robust Representation Learning

no code implementations ICCV 2021 Boxiao Liu, Guanglu Song, Manyuan Zhang, Haihang You, Yu Liu

When collaborated with the popular ArcFace on million-level data representation learning, we found that the switchable manner in SKH can effectively eliminate the gradient conflict generated by real-world label noise on a single K-class hyperplane.

Representation Learning

Precision test of statistical dynamics with state-to-state ultracold chemistry

no code implementations31 Dec 2020 Yu Liu, Ming-Guang Hu, Matthew A. Nichols, Dongzheng Yang, Daiqian Xie, Hua Guo, Kang-Kuen Ni

Chemical reactions represent a class of quantum problems that challenge both the current theoretical understanding and computational capabilities.

Chemical Physics Atomic Physics Quantum Physics

High Fermi velocities and small cyclotron masses in LaAlGe

no code implementations9 Dec 2020 Zhixiang Hu, Qianheng Du, Yu Liu, D. Graf, C. Petrovic

We report quantum oscillation measurements of LaAlGe, a Lorentz-violating type-II Weyl semimetal with tilted Weyl cones.

Mesoscale and Nanoscale Physics Materials Science

Electronic properties of InAs/EuS/Al hybrid nanowires

no code implementations12 Nov 2020 Chun-Xiao Liu, Sergej Schuwalow, Yu Liu, Kostas Vilkelis, A. L. R. Manesco, P. Krogstrup, Michael Wimmer

We study the electronic properties of InAs/EuS/Al heterostructures as explored in a recent experiment [S. Vaitiekenas \emph{et al.}, Nat.

Mesoscale and Nanoscale Physics

On the Exploration of Incremental Learning for Fine-grained Image Retrieval

no code implementations15 Oct 2020 Wei Chen, Yu Liu, Weiping Wang, Tinne Tuytelaars, Erwin M. Bakker, Michael Lew

On the other hand, fine-tuning the learned representation only with the new classes leads to catastrophic forgetting.

Image Retrieval Incremental Learning

MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings

no code implementations14 Oct 2020 Kai Wang, Yu Liu, Qian Ma, Quan Z. Sheng

Link prediction based on knowledge graph embeddings (KGE) aims to predict new triples to automatically construct knowledge graphs (KGs).

Knowledge Distillation Knowledge Graph Completion +3

Image Retrieval for Structure-from-Motion via Graph Convolutional Network

no code implementations17 Sep 2020 Shen Yan, Yang Pen, Shiming Lai, Yu Liu, Maojun Zhang

Conventional image retrieval techniques for Structure-from-Motion (SfM) suffer from the limit of effectively recognizing repetitive patterns and cannot guarantee to create just enough match pairs with high precision and high recall.

Image Retrieval Structure from Motion

Discriminability Distillation in Group Representation Learning

no code implementations ECCV 2020 Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu

We show the discrimiability knowledge has good properties that can be distilled by a light-weight distillation network and can be generalized on the unseen target set.

Representation Learning

Single Cell Transcriptome Research in Human Placenta

no code implementations7 Aug 2020 Hui Li, Qianhui Huang, Yu Liu, Lana X Garmire

Human placenta is a complex and heterogeneous organ interfacing between the mother and the fetus that supports fetal development.

Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification

1 code implementation6 Aug 2020 Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

To solve the problem, we present a carefully designed dual Gaussian-based variational auto-encoder (DG-VAE), which disentangles an identity-discriminable and an identity-ambiguous cross-modality feature subspace, following a mixture-of-Gaussians (MoG) prior and a standard Gaussian distribution prior, respectively.

Person Re-Identification Variational Inference

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

no code implementations20 Jul 2020 Haisheng Su, Jinyuan Feng, Hao Shao, Zhenyu Jiang, Manyuan Zhang, Wei Wu, Yu Liu, Hongsheng Li, Junjie Yan

Specifically, in order to generate high-quality proposals, we consider several factors including the video feature encoder, the proposal generator, the proposal-proposal relations, the scale imbalance, and ensemble strategy.

Temporal Action Localization

Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

1 code implementation8 Jul 2020 Yu Liu, Quanming Yao, Yong Li

With the rapid development of knowledge bases (KBs), link prediction task, which completes KBs with missing facts, has been broadly studied in especially binary relational KBs (a. k. a knowledge graph) with powerful tensor decomposition related methods.

Link Prediction Tensor Decomposition

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

1 code implementation16 Jun 2020 Siyu Chen, Junting Pan, Guanglu Song, Manyuan Zhang, Hao Shao, Ziyi Lin, Jing Shao, Hongsheng Li, Yu Liu

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020.

Spatio-Temporal Action Localization Temporal Action Localization

Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

1 code implementation CVPR 2021 Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li

We propose to explicitly model the Actor-Context-Actor Relation, which is the relation between two actors based on their interactions with the context.

Ranked #2 on Spatio-Temporal Action Localization on AVA-Kinetics (using extra training data)

Action Detection Spatio-Temporal Action Localization +2

A novel multimodal approach for hybrid brain-computer interface

1 code implementation25 Apr 2020 Zhe Sun, Zihao Huang, Feng Duan, Yu Liu

It has been already shown in literature that the hybrid of EEG and NIRS has better results than their respective individual signals.

Human-Computer Interaction Signal Processing

Change Detection in Heterogeneous Optical and SAR Remote Sensing Images via Deep Homogeneous Feature Fusion

no code implementations8 Apr 2020 Xiao Jiang, Gang Li, Yu Liu, Xiao-Ping Zhang, You He

To solve this problem, this paper presents a new homogeneous transformation model termed deep homogeneous feature fusion (DHFF) based on image style transfer (IST).

Style Transfer

Anisotropic Convolutional Networks for 3D Semantic Scene Completion

1 code implementation CVPR 2020 Jie Li, Kai Han, Peng Wang, Yu Liu, Xia Yuan

In contrast to the standard 3D convolution that is limited to a fixed 3D receptive field, our module is capable of modeling the dimensional anisotropy voxel-wisely.

DPGN: Distribution Propagation Graph Network for Few-shot Learning

1 code implementation CVPR 2020 Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu

To combine the distribution-level relations and instance-level relations for all examples, we construct a dual complete graph network which consists of a point graph and a distribution graph with each node standing for an example.

Few-Shot Learning

Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images

1 code implementation CVPR 2020 Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu, Xiaogang Wang

Though face rotation has achieved rapid progress in recent years, the lack of high-quality paired training data remains a great hurdle for existing methods.

3D FACE MODELING Data Augmentation +1

1st Place Solutions for OpenImage2019 -- Object Detection and Instance Segmentation

2 code implementations17 Mar 2020 Yu Liu, Guanglu Song, Yuhang Zang, Yan Gao, Enze Xie, Junjie Yan, Chen Change Loy, Xiaogang Wang

Given such good instance bounding box, we further design a simple instance-level semantic segmentation pipeline and achieve the 1st place on the segmentation challenge.

General Classification Instance Segmentation +3

KPNet: Towards Minimal Face Detector

no code implementations17 Mar 2020 Guanglu Song, Yu Liu, Yuhang Zang, Xiaogang Wang, Biao Leng, Qingsheng Yuan

The small receptive field and capacity of minimal neural networks limit their performance when using them to be the backbone of detectors.

Face Detection

Revisiting the Sibling Head in Object Detector

2 code implementations CVPR 2020 Guanglu Song, Yu Liu, Xiaogang Wang

The ``shared head for classification and localization'' (sibling head), firstly denominated in Fast RCNN~\cite{girshick2015fast}, has been leading the fashion of the object detection community in the past five years.

Ranked #43 on Object Detection on COCO test-dev (using extra training data)

Classification General Classification +1

Top-1 Solution of Multi-Moments in Time Challenge 2019

1 code implementation12 Mar 2020 Manyuan Zhang, Hao Shao, Guanglu Song, Yu Liu, Junjie Yan

In this technical report, we briefly introduce the solutions of our team 'Efficient' for the Multi-Moments in Time challenge in ICCV 2019.

Action Recognition Video Understanding

3D Gated Recurrent Fusion for Semantic Scene Completion

no code implementations17 Feb 2020 Yu Liu, Jie Li, Qingsen Yan, Xia Yuan, Chunxia Zhao, Ian Reid, Cesar Cadena

This paper tackles the problem of data fusion in the semantic scene completion (SSC) task, which can simultaneously deal with semantic labeling and scene completion.

Scene Understanding

Temporal Interlacing Network

4 code implementations17 Jan 2020 Hao Shao, Shengju Qian, Yu Liu

In this way, a heavy temporal model is replaced by a simple interlacing operator.

Optical Flow Estimation Video Understanding

Understanding the mesoscopic scaling patterns within cities

1 code implementation2 Jan 2020 Lei Dong, Zhou Huang, Jiang Zhang, Yu Liu

Understanding quantitative relationships between urban elements is crucial for a wide range of applications.

Physics and Society

Search to Distill: Pearls are Everywhere but not the Eyes

no code implementations CVPR 2020 Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang

Standard Knowledge Distillation (KD) approaches distill the knowledge of a cumbersome teacher model into the parameters of a student model with a pre-defined architecture.

Ensemble Learning Face Recognition +3

Learning Where to Focus for Efficient Video Object Detection

1 code implementation ECCV 2020 Zhengkai Jiang, Yu Liu, Ceyuan Yang, Jihao Liu, Peng Gao, Qian Zhang, Shiming Xiang, Chunhong Pan

Transferring existing image-based detectors to the video is non-trivial since the quality of frames is always deteriorated by part occlusion, rare pose, and motion blur.

Optical Flow Estimation Video Object Detection

Gradient Information Guided Deraining with A Novel Network and Adversarial Training

no code implementations9 Oct 2019 Yinglong Wang, Haokui Zhang, Yu Liu, Qinfeng Shi, Bing Zeng

However, the existing methods usually do not have good generalization ability, which leads to the fact that almost all of existing methods have a satisfied performance on removing a specific type of rain streaks, but may have a relatively poor performance on other types of rain streaks.

Rain Removal

Differentiable Kernel Evolution

no code implementations ICCV 2019 Yu Liu, Jihao Liu, Ailing Zeng, Xiaogang Wang

This paper proposes a differentiable kernel evolution (DKE) algorithm to find a better layer-operator for the convolutional neural network.

Object Classification Object Detection

Boosting Throughput and Efficiency of Hardware Spiking Neural Accelerators using Time Compression Supporting Multiple Spike Codes

no code implementations10 Sep 2019 Changqing Xu, Wenrui Zhang, Yu Liu, Peng Li

Using spiking speech and image recognition datasets, we demonstrate the feasibility of supporting large time compression ratios of up to 16x, delivering up to 15. 93x, 13. 88x, and 86. 21x improvements in throughput, energy dissipation, the tradeoffs between hardware area, runtime, energy, and classification accuracy, respectively based on different spike codes on a Xilinx Zynq-7000 FPGA.

Towards Flops-constrained Face Recognition

1 code implementation2 Sep 2019 Yu Liu, Guanglu Song, Manyuan Zhang, Jihao Liu, Yucong Zhou, Junjie Yan

Large scale face recognition is challenging especially when the computational budget is limited.

Face Recognition

In defense of OSVOS

no code implementations19 Aug 2019 Yu Liu, Yutong Dai, Anh-Dzung Doan, Lingqiao Liu, Ian Reid

Through adding a common module, video loss, which we formulate with various forms of constraints (including weighted BCE loss, high-dimensional triplet loss, as well as a novel mixed instance-aware video loss), to train the parent network in the step (2), the network is then better prepared for the step (3), i. e. online fine-tuning on the target instance.

Depth Estimation Optical Flow Estimation +4

Scalable Place Recognition Under Appearance Change for Autonomous Driving

no code implementations ICCV 2019 Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin, Yu Liu, Thanh-Toan Do, Ian Reid

Our experiments show that, compared to state-of-the-art techniques, our method has much greater potential for large-scale place recognition for autonomous driving.

Autonomous Driving Visual Place Recognition

Use of OWL and Semantic Web Technologies at Pinterest

no code implementations3 Jul 2019 Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu, Mark A. Musen, Csongor I. Nyulas, Evelyn Obamos, Dhananjay Shrouty, David Temple

In this paper, we present the engineering of an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph.

From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

no code implementations6 Jun 2019 Yu Liu, Li Deng, Jianshu Chen, Chang Wen Chen

To remove the need for the parallel training corpora has practical significance for real-world applications, and it is one of the main goals of unsupervised learning.

Classification General Classification +4

Extracting human emotions at different places based on facial expressions and spatial clustering analysis

no code implementations6 May 2019 Yuhao Kang, Qingyuan Jia, Song Gao, Xiaohuan Zeng, Yueyao Wang, Stephan Angsuesser, Yu Liu, Xinyue Ye, Teng Fei

In this study, a novel framework for extracting human emotions from large-scale georeferenced photos at different places is proposed.

Knowledge Distillation via Route Constrained Optimization

1 code implementation ICCV 2019 Xiao Jin, Baoyun Peng, Yi-Chao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Xiaolin Hu

However, we find that the representation of a converged heavy model is still a strong constraint for training a small student model, which leads to a high lower bound of congruence loss.

Curriculum Learning Face Recognition +1

Correlation Congruence for Knowledge Distillation

2 code implementations ICCV 2019 Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yi-Chao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang

Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level.

Face Recognition Image Classification +3

Conditional Adversarial Generative Flow for Controllable Image Synthesis

no code implementations CVPR 2019 Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li

Flow-based generative models show great potential in image synthesis due to its reversible pipeline and exact log-likelihood target, yet it suffers from weak ability for conditional image synthesis, especially for multi-label or unaware conditions.

Image Generation

RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion

no code implementations CVPR 2019 Jie Li, Yu Liu, Dong Gong, Qinfeng Shi, Xia Yuan, Chunxia Zhao, Ian Reid

RGB images differentiate from depth images as they carry more details about the color and texture information, which can be utilized as a vital complementary to depth for boosting the performance of 3D semantic scene completion (SSC).

Scene Labeling

Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

no code implementations12 Jan 2019 Yu Liu, Lingqiao Liu, Hamid Rezatofighi, Thanh-Toan Do, Qinfeng Shi, Ian Reid

As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years.

Object Detection

Derivative Estimation in Random Design

no code implementations NeurIPS 2018 Yu Liu, Kris De Brabanter

We propose a nonparametric derivative estimation method for random design without having to estimate the regression function.

RGB-D Based Action Recognition with Light-weight 3D Convolutional Networks

no code implementations24 Nov 2018 Haokui Zhang, Ying Li, Peng Wang, Yu Liu, Chunhua Shen

Different from RGB videos, depth data in RGB-D videos provide key complementary information for tristimulus visual data which potentially could achieve accuracy improvement for action recognition.

Action Recognition

How to improve the interpretability of kernel learning

no code implementations21 Nov 2018 Jinwei Zhao, Qizhou Wang, YuFei Wang, Yu Liu, Zhenghao Shi, Xinhong Hei

In this paper, a quantitative index of the interpretability is proposed and its rationality is proved, and equilibrium problem between the interpretability and the generalization performance is analyzed.

How far from automatically interpreting deep learning

no code implementations19 Nov 2018 Jinwei Zhao, Qizhou Wang, YuFei Wang, Xinhong Hei, Yu Liu

In other words, there is a gap between the deep learning model and the cognitive mode.

Gradient Harmonized Single-stage Detector

7 code implementations13 Nov 2018 Buyu Li, Yu Liu, Xiaogang Wang

Despite the great success of two-stage detectors, single-stage detector is still a more elegant and efficient way, yet suffers from the two well-known disharmonies during training, i. e. the huge difference in quantity between positive and negative examples as well as between easy and hard examples.

General Classification Object Detection

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction

7 code implementations12 Nov 2018 Ling Zhao, Yujiao Song, Chao Zhang, Yu Liu, Pu Wang, Tao Lin, Min Deng, Haifeng Li

However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence and temporal dependence.

Traffic Prediction

Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection

3 code implementations22 Oct 2018 Enqiang Guo, Xinsha Fu, Jiawei Zhu, Min Deng, Yu Liu, Qing Zhu, Haifeng Li

A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled.

Scene Change Detection

Transductive Centroid Projection for Semi-supervised Large-scale Recognition

no code implementations ECCV 2018 Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang

It is inspired by the observation of the weights in classification layer (called extit{anchors}) converge to the central direction of each class in hyperspace.

General Classification

Knowledge Graph Embedding with Entity Neighbors and Deep Memory Network

no code implementations11 Aug 2018 Kai Wang, Yu Liu, Xiujuan Xu, Dan Lin

Knowledge Graph Embedding (KGE) aims to represent entities and relations of knowledge graph in a low-dimensional continuous vector space.

Knowledge Graph Embedding

Talking Face Generation by Adversarially Disentangled Audio-Visual Representation

1 code implementation20 Jul 2018 Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang

Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech.

Lip Reading Talking Face Generation +1

Improved Techniques for Learning to Dehaze and Beyond: A Collective Study

1 code implementation30 Jun 2018 Yu Liu, Guanlong Zhao, Boyuan Gong, Yang Li, Ritu Raj, Niraj Goel, Satya Kesav, Sandeep Gottimukkala, Zhangyang Wang, Wenqi Ren, DaCheng Tao

Here we explore two related but important tasks based on the recently released REalistic Single Image DEhazing (RESIDE) benchmark dataset: (i) single image dehazing as a low-level image restoration problem; and (ii) high-level visual understanding (e. g., object detection) of hazy images.

Image Dehazing Image Restoration +2

MoNet: Deep Motion Exploitation for Video Object Segmentation

no code implementations CVPR 2018 Huaxin Xiao, Jiashi Feng, Guosheng Lin, Yu Liu, Maojun Zhang

In this paper, we propose a novel MoNet model to deeply exploit motion cues for boosting video object segmentation performance from two aspects, i. e., frame representation learning and segmentation refinement.

Optical Flow Estimation Representation Learning +3

PAD-Net: A Perception-Aided Single Image Dehazing Network

1 code implementation8 May 2018 Yu Liu, Guanlong Zhao

In this work, we investigate the possibility of replacing the $\ell_2$ loss with perceptually derived loss functions (SSIM, MS-SSIM, etc.)

Image Dehazing MS-SSIM +2

Beyond Trade-off: Accelerate FCN-based Face Detector with Higher Accuracy

no code implementations CVPR 2018 Guanglu Song, Yu Liu, Ming Jiang, Yujie Wang, Junjie Yan, Biao Leng

Fully convolutional neural network (FCN) has been dominating the game of face detection task for a few years with its congenital capability of sliding-window-searching with shared kernels, which boiled down all the redundant calculation, and most recent state-of-the-art methods such as Faster-RCNN, SSD, YOLO and FPN use FCN as their backbone.

Face Detection

The artificial ecosystem: number soup (part II)

no code implementations12 Jan 2018 Yu Liu

This paper is a follow-up work about the artificial ecosystem model: number soup (Liu and Sumpter, J. Royal Soc.

Region-based Quality Estimation Network for Large-scale Person Re-identification

no code implementations23 Nov 2017 Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai

One of the major restrictions on the performance of video-based person re-id is partial noise caused by occlusion, blur and illumination.

Large-Scale Person Re-Identification

Transferable Semi-supervised Semantic Segmentation

no code implementations18 Nov 2017 Huaxin Xiao, Yunchao Wei, Yu Liu, Maojun Zhang, Jiashi Feng

The performance of deep learning based semantic segmentation models heavily depends on sufficient data with careful annotations.

Semi-Supervised Semantic Segmentation

Learning a Recurrent Residual Fusion Network for Multimodal Matching

no code implementations ICCV 2017 Yu Liu, Yanming Guo, Erwin M. Bakker, Michael S. Lew

A major challenge in matching between vision and language is that they typically have completely different features and representations.

Recurrent Scale Approximation for Object Detection in CNN

1 code implementation ICCV 2017 Yu Liu, Hongyang Li, Junjie Yan, Fangyin Wei, Xiaogang Wang, Xiaoou Tang

To further increase efficiency and accuracy, we (a): design a scale-forecast network to globally predict potential scales in the image since there is no need to compute maps on all levels of the pyramid.

Face Detection Object Detection

MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data?

no code implementations29 Jul 2017 Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang

We then compare the performance of the top winning code available from Kaggle with that of running machine learning clouds from both Azure and Amazon on mlbench.

General Classification

Quality Aware Network for Set to Set Recognition

1 code implementation CVPR 2017 Yu Liu, Junjie Yan, Wanli Ouyang

In this paper, the quality aware network (QAN) is proposed to confront this problem, where the quality of each sample can be automatically learned although such information is not explicitly provided in the training stage.

Face Verification Person Re-Identification

Unsupervised Sequence Classification using Sequential Output Statistics

no code implementations NeurIPS 2017 Yu Liu, Jianshu Chen, Li Deng

Although it is harder to optimize in its functional form, a stochastic primal-dual gradient method is developed to effectively solve the problem.

Classification General Classification

Learning Deep Features via Congenerous Cosine Loss for Person Recognition

1 code implementation22 Feb 2017 Yu Liu, Hongyang Li, Xiaogang Wang

Person recognition aims at recognizing the same identity across time and space with complicated scenes and similar appearance.

Person Recognition

Zoom Out-and-In Network with Recursive Training for Object Proposal

1 code implementation19 Feb 2017 Hongyang Li, Yu Liu, Wanli Ouyang, Xiaogang Wang

In this paper, we propose a zoom-out-and-in network for generating object proposals.

On the Exploration of Convolutional Fusion Networks for Visual Recognition

no code implementations16 Nov 2016 Yu Liu, Yanming Guo, Michael S. Lew

Despite recent advances in multi-scale deep representations, their limitations are attributed to expensive parameters and weak fusion modules.

Image Retrieval Scene Recognition

Combinatorial Multi-Armed Bandit with General Reward Functions

no code implementations NeurIPS 2016 Wei Chen, Wei Hu, Fu Li, Jian Li, Yu Liu, Pinyan Lu

Our framework enables a much larger class of reward functions such as the $\max()$ function and nonlinear utility functions.

POI: Multiple Object Tracking with High Performance Detection and Appearance Feature

no code implementations19 Oct 2016 Fengwei Yu, Wenbo Li, Quanquan Li, Yu Liu, Xiaohua Shi, Junjie Yan

In this paper, we explore the high-performance detection and deep learning based appearance feature, and show that they lead to significantly better MOT results in both online and offline setting.

Multiple Object Tracking

Crafting GBD-Net for Object Detection

1 code implementation8 Oct 2016 Xingyu Zeng, Wanli Ouyang, Junjie Yan, Hongsheng Li, Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin Yang, Zhe Wang, Hui Zhou, Xiaogang Wang

The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO.

Object Detection

Storytelling of Photo Stream with Bidirectional Multi-thread Recurrent Neural Network

no code implementations2 Jun 2016 Yu Liu, Jianlong Fu, Tao Mei, Chang Wen Chen

Second, by using sGRU as basic units, the BMRNN is trained to align the local storylines into the global sequential timeline.

Video Captioning Visual Storytelling

Learning Relaxed Deep Supervision for Better Edge Detection

no code implementations CVPR 2016 Yu Liu, Michael S. Lew

We consider these false positives in the supervision, and are able to achieve high performance for better edge detection.

BSDS500 Edge Detection

Modulation Classification via Gibbs Sampling Based on a Latent Dirichlet Bayesian Network

no code implementations4 Aug 2014 Yu Liu, Osvaldo Simeone, Alexander M. Haimovich, Wei Su

A novel Bayesian modulation classification scheme is proposed for a single-antenna system over frequency-selective fading channels.

Classification General Classification

Delineating Intra-Urban Spatial Connectivity Patterns by Travel-Activities: A Case Study of Beijing, China

no code implementations16 Jul 2014 Chaogui Kang, Yu Liu, Lun Wu

Travel activities have been widely applied to quantify spatial interactions between places, regions and nations.

Physics and Society Social and Information Networks

Cannot find the paper you are looking for? You can Submit a new open access paper.