Search Results for author: Jianqiang Huang

Found 55 papers, 26 papers with code

Momentum Batch Normalization for Deep Learning with Small Batch Size

no code implementations ECCV 2020 Hongwei Yong, Jianqiang Huang, Deyu Meng, Xian-Sheng Hua, Lei Zhang

To make a deeper understanding of BN, in this work we prove that BN actually introduces a certain level of noise into the sample mean and variance during the training process, while the noise level depends only on the batch size.

Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection

no code implementations14 Apr 2022 Ze Chen, Zhihang Fu, Jianqiang Huang, Mingyuan Tao, Rongxin Jiang, Xiang Tian, Yaowu Chen, Xian-Sheng Hua

The likelihood maps generated by the SLV module are used to supervise the feature learning of the backbone network, encouraging the network to attend to wider and more diverse areas of the image.

Multiple Instance Learning Region Proposal +2

Dynamic Supervisor for Cross-dataset Object Detection

no code implementations1 Apr 2022 Ze Chen, Zhihang Fu, Jianqiang Huang, Mingyuan Tao, Shengyu Li, Rongxin Jiang, Xiang Tian, Yaowu Chen, Xian-Sheng Hua

The application of cross-dataset training in object detection tasks is complicated because the inconsistency in the category range across datasets transforms fully supervised learning into semi-supervised learning.

Object Detection

Continual Learning for CTR Prediction: A Hybrid Approach

no code implementations18 Jan 2022 Ke Hu, Yi Qi, Jianqiang Huang, Jia Cheng, Jun Lei

To address this problem, we formulate CTR prediction as a continual learning task and propose COLF, a hybrid COntinual Learning Framework for CTR prediction, which has a memory-based modular architecture that is designed to adapt, learn and give predictions continuously when faced with non-stationary drifting click data streams.

Click-Through Rate Prediction Continual Learning

Deconfounded Visual Grounding

1 code implementation31 Dec 2021 Jianqiang Huang, Yu Qin, Jiaxin Qi, Qianru Sun, Hanwang Zhang

We focus on the confounding bias between language and location in the visual grounding pipeline, where we find that the bias is the major visual reasoning bottleneck.

Frame Referring Expression +2

AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020

1 code implementation25 Nov 2021 Jin Xu, Mingjian Chen, Jianqiang Huang, Xingyuan Tang, Ke Hu, Jian Li, Jia Cheng, Jun Lei

Graph Neural Networks (GNNs) have become increasingly popular and achieved impressive results in many graph-based applications.

Graph Classification Node Classification

Meta Clustering Learning for Large-scale Unsupervised Person Re-identification

no code implementations19 Nov 2021 Xin Jin, Tianyu He, Zhiheng Yin, Xu Shen, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen

Unsupervised Person Re-identification (U-ReID) with pseudo labeling recently reaches a competitive performance compared to fully-supervised ReID methods based on modern clustering algorithms.

Unsupervised Person Re-Identification

Self-Supervised Learning Disentangled Group Representation as Feature

1 code implementation NeurIPS 2021 Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang

A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics).

Colorization Contrastive Learning +1

Density-Based Clustering with Kernel Diffusion

no code implementations11 Oct 2021 Chao Zheng, Yingjie Chen, Chong Chen, Jianqiang Huang, Xian-Sheng Hua

Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC.

Face Clustering

Networked Time Series Prediction with Incomplete Data

no code implementations5 Oct 2021 Yichen Zhu, Mengtian Zhang, Bo Jiang, Haiming Jin, Jianqiang Huang, Xinbing Wang

We propose NETS-ImpGAN, a novel deep learning framework that can be trained on incomplete data with missing values in both history and future.

Time Series Time Series Prediction

Unleash the Potential of Adaptation Models via Dynamic Domain Labels

no code implementations29 Sep 2021 Xin Jin, Tianyu He, Xu Shen, Songhua Wu, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua

In this paper, we propose an embarrassing simple yet highly effective adversarial domain adaptation (ADA) method for effectively training models for alignment.

Domain Adaptation

AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational Data

1 code implementation9 Sep 2021 Zhipeng Luo, Zhixing He, Jin Wang, Manqing Dong, Jianqiang Huang, Mingjian Chen, Bohang Zheng

Temporal relational data, perhaps the most commonly used data type in industrial machine learning applications, needs labor-intensive feature engineering and data analyzing for giving precise model predictions.

AutoML Feature Engineering

Improving 3D Object Detection with Channel-wise Transformer

1 code implementation ICCV 2021 Hualian Sheng, Sijia Cai, YuAn Liu, Bing Deng, Jianqiang Huang, Xian-Sheng Hua, Min-Jian Zhao

Though 3D object detection from point clouds has achieved rapid progress in recent years, the lack of flexible and high-performance proposal refinement remains a great hurdle for existing state-of-the-art two-stage detectors.

3D Object Detection Region Proposal

Aug3D-RPN: Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depth

no code implementations28 Jul 2021 Chenhang He, Jianqiang Huang, Xian-Sheng Hua, Lei Zhang

Current geometry-based monocular 3D object detection models can efficiently detect objects by leveraging perspective geometry, but their performance is limited due to the absence of accurate depth information.

Depth Estimation Monocular 3D Object Detection

Revisiting Knowledge Distillation: An Inheritance and Exploration Framework

1 code implementation CVPR 2021 Zhen Huang, Xu Shen, Jun Xing, Tongliang Liu, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua

The inheritance part is learned with a similarity loss to transfer the existing learned knowledge from the teacher model to the student model, while the exploration part is encouraged to learn representations different from the inherited ones with a dis-similarity loss.

Knowledge Distillation

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

1 code implementation25 May 2021 Xiao Luo, Daqing Wu, Chong Chen, Jinwen Ma, Minghua Deng, Chen Shen, Jianqiang Huang, Xian-Sheng Hua

Besides, CHCF integrates criterion learning and user preference learning into a unified framework, which can be trained jointly for the interaction prediction on target behavior.

Collaborative Filtering Metric Learning +1

Discriminative-Generative Dual Memory Video Anomaly Detection

no code implementations29 Apr 2021 Xin Guo, Zhongming Jin, Chong Chen, Helei Nie, Jianqiang Huang, Deng Cai, Xiaofei He, Xiansheng Hua

In this paper, we propose a DiscRiminative-gEnerative duAl Memory (DREAM) anomaly detection model to take advantage of a few anomalies and solve data imbalance.

Anomaly Detection Frame

Graph Contrastive Clustering

1 code implementation ICCV 2021 Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua

On the other hand, a novel graph-based contrastive learning strategy is proposed to learn more compact clustering assignments.

Contrastive Learning

Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation

no code implementations2 Apr 2021 Zilong Huang, Wentian Hao, Xinggang Wang, Mingyuan Tao, Jianqiang Huang, Wenyu Liu, Xian-Sheng Hua

Despite their success for semantic segmentation, convolutional neural networks are ill-equipped for incremental learning, \ie, adapting the original segmentation model as new classes are available but the initial training data is not retained.

Incremental Learning Semantic Segmentation

Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization

1 code implementation29 Mar 2021 Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen

Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.

Gait Recognition Person Re-Identification

The Blessings of Unlabeled Background in Untrimmed Videos

1 code implementation CVPR 2021 YuAn Liu, Jingyuan Chen, Zhenfang Chen, Bing Deng, Jianqiang Huang, Hanwang Zhang

The key challenge is how to distinguish the action of interest segments from the background, which is unlabelled even on the video-level.

14 Weakly-supervised Temporal Action Localization +1

Dense Interaction Learning for Video-based Person Re-identification

no code implementations ICCV 2021 Tianyu He, Xin Jin, Xu Shen, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua

The CNN encoder is responsible for efficiently extracting discriminative spatial features while the DI decoder is designed to densely model spatial-temporal inherent interaction across frames.

Video-Based Person Re-Identification

VideoFlow: A Framework for Building Visual Analysis Pipelines

no code implementations1 Jan 2021 Yue Wu, Jianqiang Huang, Jiangjie Zhen, Guokun Wang, Chen Shen, Chang Zhou, Xian-Sheng Hua

The past years have witnessed an explosion of deep learning frameworks like PyTorch and TensorFlow since the success of deep neural networks.

Video Object Segmentation With Dynamic Memory Networks and Adaptive Object Alignment

1 code implementation ICCV 2021 Shuxian Liang, Xu Shen, Jianqiang Huang, Xian-Sheng Hua

In this paper, we propose a novel solution for object-matching based semi-supervised video object segmentation, where the target object masks in the first frame are provided.

Frame Semantic Segmentation +2

3D Local Convolutional Neural Networks for Gait Recognition

1 code implementation ICCV 2021 Zhen Huang, Dixiu Xue, Xu Shen, Xinmei Tian, Houqiang Li, Jianqiang Huang, Xian-Sheng Hua

Second, different body parts possess different scales, and even the same part in different frames can appear at different locations and scales.

Frame Gait Recognition

Learning to Generate Content-Aware Dynamic Detectors

no code implementations8 Dec 2020 Junyi Feng, Jiashen Hua, Baisheng Lai, Jianqiang Huang, Xi Li, Xian-Sheng Hua

To the best of our knowledge, our CADDet is the first work to introduce dynamic routing mechanism in object detection.

Object Detection

Tracklets Predicting Based Adaptive Graph Tracking

no code implementations18 Oct 2020 Chaobing Shan, Chunbo Wei, Bing Deng, Jianqiang Huang, Xian-Sheng Hua, Xiaoliang Cheng, Kewei Liang

It re-extracts the features of the tracklets in the current frame based on motion predicting, which is the key to solve the problem of features inconsistent.

Autonomous Driving Frame +2

CIMON: Towards High-quality Hash Codes

no code implementations15 Oct 2020 Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma, Zhongming Jin, Jianqiang Huang, Xian-Sheng Hua

However, due to the inefficient representation ability of the pre-trained model, many false positives and negatives in local semantic similarity will be introduced and lead to error propagation during the hash code learning.

Image Augmentation Semantic Similarity +1

PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph Generation

1 code implementation2 Sep 2020 Shaotian Yan, Chen Shen, Zhongming Jin, Jianqiang Huang, Rongxin Jiang, Yaowu Chen, Xian-Sheng Hua

Today, scene graph generation(SGG) task is largely limited in realistic scenarios, mainly due to the extremely long-tailed bias of predicate annotation distribution.

Graph Generation Unbiased Scene Graph Generation

Apparel-invariant Feature Learning for Apparel-changed Person Re-identification

no code implementations14 Aug 2020 Zhengxu Yu, Yilun Zhao, Bin Hong, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua

Therefore, it is critical to learn an apparel-invariant person representation under cases like cloth changing or several persons wearing similar clothes.

Person Re-Identification Representation Learning

Out-of-distribution Generalization via Partial Feature Decorrelation

no code implementations30 Jul 2020 Xin Guo, Zhengxu Yu, Chao Xiang, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua

Most deep-learning-based image classification methods assume that all samples are generated under an independent and identically distributed (IID) setting.

Classification General Classification +3

Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles

no code implementations13 Jul 2020 Jer Shyuan Ng, Wei Yang Bryan Lim, Hong-Ning Dai, Zehui Xiong, Jianqiang Huang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

The simulation results show that the grand coalition, where all UAVs join a single coalition, is not always stable due to the profit-maximizing behavior of the UAVs.

Networking and Internet Architecture Signal Processing

Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach

no code implementations8 Apr 2020 Wei Yang Bryan Lim, Jianqiang Huang, Zehui Xiong, Jiawen Kang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (AI) based models to be built.

Signal Processing Networking and Internet Architecture

Gradient Centralization: A New Optimization Technique for Deep Neural Networks

7 code implementations ECCV 2020 Hongwei Yong, Jianqiang Huang, Xian-Sheng Hua, Lei Zhang

It has been shown that using the first and second order statistics (e. g., mean and variance) to perform Z-score standardization on network activations or weight vectors, such as batch normalization (BN) and weight standardization (WS), can improve the training performance.

Fine-Grained Image Classification General Classification

A Survey on Deep Hashing Methods

no code implementations4 Mar 2020 Xiao Luo, Haixin Wang, Daqing Wu, Chong Chen, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua

Nearest neighbor search aims to obtain the samples in the database with the smallest distances from them to the queries, which is a basic task in a range of fields, including computer vision and data mining.

Domain Adaptation Quantization +2

Visual Commonsense R-CNN

2 code implementations CVPR 2020 Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun

We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA.

Image Captioning Representation Learning +2

Unbiased Scene Graph Generation from Biased Training

5 code implementations CVPR 2020 Kaihua Tang, Yulei Niu, Jianqiang Huang, Jiaxin Shi, Hanwang Zhang

Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e. g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach".

Causal Inference Graph Generation +2

Towards Precise Intra-camera Supervised Person Re-identification

no code implementations12 Feb 2020 Menglin Wang, Baisheng Lai, Haokun Chen, Jianqiang Huang, Xiaojin Gong, Xian-Sheng Hua

Our approach performs even comparable to state-of-the-art fully supervised methods in two of the datasets.

Person Re-Identification

Two Causal Principles for Improving Visual Dialog

1 code implementation CVPR 2020 Jiaxin Qi, Yulei Niu, Jianqiang Huang, Hanwang Zhang

This paper unravels the design tricks adopted by us, the champion team MReaL-BDAI, for Visual Dialog Challenge 2019: two causal principles for improving Visual Dialog (VisDial).

Visual Dialog

Quantization Networks

1 code implementation CVPR 2019 Jiwei Yang, Xu Shen, Jun Xing, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua

The proposed quantization function can be learned in a lossless and end-to-end manner and works for any weights and activations of neural networks in a simple and uniform way.

Image Classification Object Detection +1

Neural News Recommendation with Heterogeneous User Behavior

no code implementations IJCNLP 2019 Chuhan Wu, Fangzhao Wu, Mingxiao An, Tao Qi, Jianqiang Huang, Yongfeng Huang, Xing Xie

In the user representation module, we propose an attentive multi-view learning framework to learn unified representations of users from their heterogeneous behaviors such as search queries, clicked news and browsed webpages.

MULTI-VIEW LEARNING News Recommendation

Progressive Transfer Learning

1 code implementation7 Aug 2019 Zhengxu Yu, Dong Shen, Zhongming Jin, Jianqiang Huang, Deng Cai, Xian-Sheng Hua

Model fine-tuning is a widely used transfer learning approach in person Re-identification (ReID) applications, which fine-tuning a pre-trained feature extraction model into the target scenario instead of training a model from scratch.

Image Classification Person Re-Identification +1

NPA: Neural News Recommendation with Personalized Attention

no code implementations12 Jul 2019 Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie

Since different words and different news articles may have different informativeness for representing news and users, we propose to apply both word- and news-level attention mechanism to help our model attend to important words and news articles.

Informativeness News Recommendation

Neural News Recommendation with Attentive Multi-View Learning

4 code implementations12 Jul 2019 Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie

In the user encoder we learn the representations of users based on their browsed news and apply attention mechanism to select informative news for user representation learning.

MULTI-VIEW LEARNING News Recommendation +2

Deep Active Learning for Video-based Person Re-identification

no code implementations14 Dec 2018 Menglin Wang, Baisheng Lai, Zhongming Jin, Xiaojin Gong, Jianqiang Huang, Xian-Sheng Hua

With the gained annotations of the actively selected candidates, the tracklets' pesudo labels are updated by label merging and further used to re-train our re-ID model.

Active Learning Video-Based Person Re-Identification

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

Homocentric Hypersphere Feature Embedding for Person Re-identification

no code implementations24 Apr 2018 Wangmeng Xiang, Jianqiang Huang, Xianbiao Qi, Xian-Sheng Hua, Lei Zhang

Person re-identification (Person ReID) is a challenging task due to the large variations in camera viewpoint, lighting, resolution, and human pose.

Person Re-Identification

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