Search Results for author: Jinjun Wang

Found 32 papers, 8 papers with code

Single-Shot and Multi-Shot Feature Learning for Multi-Object Tracking

no code implementations17 Nov 2023 Yizhe Li, Sanping Zhou, Zheng Qin, Le Wang, Jinjun Wang, Nanning Zheng

In this paper, we propose a simple yet effective two-stage feature learning paradigm to jointly learn single-shot and multi-shot features for different targets, so as to achieve robust data association in the tracking process.

Multi-Object Tracking

Understanding the Overfitting of the Episodic Meta-training

no code implementations29 Jun 2023 Siqi Hui, Sanping Zhou, Ye Deng, Jinjun Wang

Specifically, we select the teacher model as the one with the best validation accuracy during meta-training and restrict the symmetric Kullback-Leibler (SKL) divergence between the output distribution of the linear classifier of the teacher model and that of the student model.

Knowledge Distillation

Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning

no code implementations3 Jun 2023 Long Chen, Siyu Teng, Bai Li, Xiaoxiang Na, Yuchen Li, Zixuan Li, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their promise for enhanced safety, efficiency, and economic benefits.

Autonomous Driving Ethics

T-former: An Efficient Transformer for Image Inpainting

2 code implementations12 May 2023 Ye Deng, Siqi Hui, Sanping Zhou, Deyu Meng, Jinjun Wang

And based on this attention, a network called $T$-former is designed for image inpainting.

Image Inpainting Long-range modeling

Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

no code implementations12 May 2023 Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions.

Autonomous Driving Ethics

Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

no code implementations30 Mar 2023 Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.

Autonomous Driving Ethics

Auxiliary Loss Reweighting for Image Inpainting

1 code implementation14 Nov 2021 Siqi Hui, Sanping Zhou, Ye Deng, Wenli Huang, Jinjun Wang

TPL and TSL are supersets of perceptual and style losses and release the auxiliary potential of standard perceptual and style losses.

Image Inpainting

Memory-Free Generative Replay For Class-Incremental Learning

1 code implementation1 Sep 2021 Xiaomeng Xin, Yiran Zhong, Yunzhong Hou, Jinjun Wang, Liang Zheng

With the absence of old task images, they often assume that old knowledge is well preserved if the classifier produces similar output on new images.

Class Incremental Learning Incremental Learning

Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection

1 code implementation12 Dec 2020 Rongye Meng, Sanping Zhou, Xingyu Wan, Mengliu Li, Jinjun Wang

The radical student uses multi-source supervision signals from the same task to update parameters, while the calm teacher uses a single-source supervision signal to update parameters.

Facial Landmark Detection

End-to-End Multi-Object Tracking with Global Response Map

no code implementations13 Jul 2020 Xingyu Wan, Jiakai Cao, Sanping Zhou, Jinjun Wang

Most existing Multi-Object Tracking (MOT) approaches follow the Tracking-by-Detection paradigm and the data association framework where objects are firstly detected and then associated.

Multi-Object Tracking Object +2

Meta Corrupted Pixels Mining for Medical Image Segmentation

no code implementations7 Jul 2020 Jixin Wang, Sanping Zhou, Chaowei Fang, Le Wang, Jinjun Wang

However the training of deep neural network requires a large amount of samples with high-quality annotations.

Image Segmentation Medical Image Segmentation +2

Multiple Object Tracking by Flowing and Fusing

no code implementations30 Jan 2020 Jimuyang Zhang, Sanping Zhou, Xin Chang, Fangbin Wan, Jinjun Wang, Yang Wu, Dong Huang

Most of Multiple Object Tracking (MOT) approaches compute individual target features for two subtasks: estimating target-wise motions and conducting pair-wise Re-Identification (Re-ID).

Multiple Object Tracking Object +2

Collaborative Attention Network for Person Re-identification

no code implementations29 Nov 2019 Wenpeng Li, Yongli Sun, Jinjun Wang, Han Xu, Xiangru Yang, Long Cui

Jointly utilizing global and local features to improve model accuracy is becoming a popular approach for the person re-identification (ReID) problem, because previous works using global features alone have very limited capacity at extracting discriminative local patterns in the obtained feature representation.

Person Re-Identification

Distributed Generative Adversarial Net

1 code implementation19 Nov 2019 Xiaoyu Wang, Ye Deng, Jinjun Wang

Recently the Generative Adversarial Network has become a hot topic.

Generative Adversarial Network

Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning

no code implementations16 Sep 2019 Qi Gao, Shaowu Pan, Hongping Wang, Runjie Wei, Jinjun Wang

Three-dimensional particle reconstruction with limited two-dimensional projections is an under-determined inverse problem that the exact solution is often difficult to be obtained.

BIG-bench Machine Learning

Frame-wise Motion and Appearance for Real-time Multiple Object Tracking

no code implementations6 May 2019 Jimuyang Zhang, Sanping Zhou, Jinjun Wang, Dong Huang

The main challenge of Multiple Object Tracking (MOT) is the efficiency in associating indefinite number of objects between video frames.

Multiple Object Tracking Object

SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection

1 code implementation29 Mar 2019 Sanping Zhou, Jimuyang Zhang, Jinjun Wang, Fei Wang, Dong Huang

In this paper, we propose a simple yet effective Siamese Edge-Enhancement Network (SE2Net) to preserve the edge structure for salient object detection.

Object object-detection +2

Video Smoke Detection Based on Deep Saliency Network

no code implementations8 Sep 2018 Gao Xu, Yongming Zhang, Qixing Zhang, Gaohua Lin, Zhong Wang, Yang Jia, Jinjun Wang

The deep feature map is combined with the saliency map to predict the existence of smoke in an image.

Fire Detection Saliency Detection

Discriminative Feature Learning with Foreground Attention for Person Re-Identification

no code implementations4 Jul 2018 Sanping Zhou, Jinjun Wang, Deyu Meng, Yudong Liang, Yihong Gong, Nanning Zheng

Specifically, a novel foreground attentive subnetwork is designed to drive the network's attention, in which a decoder network is used to reconstruct the binary mask by using a novel local regression loss function, and an encoder network is regularized by the decoder network to focus its attention on the foreground persons.

Multi-Task Learning Person Re-Identification

Deep Self-Paced Learning for Person Re-Identification

no code implementations7 Oct 2017 Sanping Zhou, Jinjun Wang, Deyu Meng, Xiaomeng Xin, Yubing Li, Yihong Gong, Nanning Zheng

In this paper, we propose a novel deep self-paced learning (DSPL) algorithm to alleviate this problem, in which we apply a self-paced constraint and symmetric regularization to help the relative distance metric training the deep neural network, so as to learn the stable and discriminative features for person Re-ID.

Person Re-Identification

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

2 code implementations5 Oct 2017 Shun Zhang, Jia-Bin Huang, Jongwoo Lim, Yihong Gong, Jinjun Wang, Narendra Ahuja, Ming-Hsuan Yang

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in scale, pose, expression, illumination, and make-up.

Clustering

Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification

no code implementations18 Aug 2017 Sanping Zhou, Jinjun Wang, Rui Shi, Qiqi Hou, Yihong Gong, Nanning Zheng

The class-identity term keeps the intra-class samples within each camera view gathering together, the relative distance term maximizes the distance between the intra-class class set and inter-class set across different camera views, and the regularization term smoothness the parameters of deep convolutional neural network (CNN).

Person Re-Identification Retrieval

Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification

no code implementations3 Jul 2017 Jiayun Wang, Sanping Zhou, Jinjun Wang, Qiqi Hou

In this paper, we present a novel deep ranking model with feature learning and fusion by learning a large adaptive margin between the intra-class distance and inter-class distance to solve the person re-identification problem.

Person Re-Identification

Point to Set Similarity Based Deep Feature Learning for Person Re-Identification

no code implementations CVPR 2017 Sanping Zhou, Jinjun Wang, Jiayun Wang, Yihong Gong, Nanning Zheng

One of the key issues for deep learning based person Re-ID is the selection of proper similarity comparison criteria, and the performance of learned features using existing criterion based on pairwise similarity is still limited, because only P2P distances are mostly considered.

Person Re-Identification

Single Image Super Resolution - When Model Adaptation Matters

no code implementations31 Mar 2017 Yudong Liang, Radu Timofte, Jinjun Wang, Yihong Gong, Nanning Zheng

The internal contents of the low resolution input image is neglected with deep modeling despite the earlier works showing the power of using such internal priors.

Image Super-Resolution

Deep Domain Adaptation Based Video Smoke Detection using Synthetic Smoke Images

no code implementations31 Mar 2017 Gao Xu, Yongming Zhang, Qixing Zhang, Gaohua Lin, Jinjun Wang

Considering that the appearance gap (dataset bias) between synthetic and real smoke images degrades significantly the performance of the trained model on the test set composed fully of real images, we build deep architectures based on domain adaptation to confuse the distributions of features extracted from synthetic and real smoke images.

Domain Adaptation

Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network

no code implementations23 Mar 2017 Yudong Liang, Ze Yang, Kai Zhang, Yihui He, Jinjun Wang, Nanning Zheng

To tackle with the second problem, a lightweight CNN architecture which has carefully designed width, depth and skip connections was proposed.

Image Super-Resolution SSIM

Person Re-Identification by Multi-Channel Parts-Based CNN With Improved Triplet Loss Function

no code implementations CVPR 2016 De Cheng, Yihong Gong, Sanping Zhou, Jinjun Wang, Nanning Zheng

Person re-identification across cameras remains a very challenging problem, especially when there are no overlapping fields of view between cameras.

Person Re-Identification

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