☆ 4.6 Article

View-aware attribute-guided network for vehicle re-identification

MULTIMEDIA SYSTEMS (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Information Systems

Towards Adaptive Consensus Graph: Multi-View Clustering via Graph Collaboration

Huibing Wang et al.

Summary: In this paper, a novel method named multi-view clustering via graph collaboration (MCGC) is proposed to uncover the correlations between multi-view data by collaboratively learning from multiple views. The method utilizes a consensus graph to reveal the essential structure of the data and directly obtains optimal clustering results without postprocessing steps.

IEEE TRANSACTIONS ON MULTIMEDIA (2023)

添加到收藏夹

Article Engineering, Electrical & Electronic

Unsupervised vehicle re-identification based on mixed sample contrastive learning

Yuefeng Wang et al.

Summary: This paper proposes a mixed sample contrastive learning framework for unsupervised vehicle re-identification, which constructs memory dictionary with discrete samples and reliable clusters. It introduces a discrete sample separation module and a mixed sample contrastive learning strategy, and proposes a discrete sample loss to update the memory dictionary dynamically during training. Extensive experiments show the favorable performance of the proposed method.

SIGNAL IMAGE AND VIDEO PROCESSING (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Multiview image generation for vehicle reidentification

Fukai Zhang et al.

Summary: This paper introduces a multi-view generative adversarial network for viewpoint normalization in vehicle ReID, showing that features of generated and original images are complementary and improving the effectiveness of vehicle re-identification.

APPLIED INTELLIGENCE (2021)

添加到收藏夹

Article Engineering, Electrical & Electronic

Robust license plate detection and recognition with automatic rectification

Degui Xiao et al.

Summary: This paper proposes a robust license plate detection and recognition framework with automatic rectification, utilizing deep learning to effectively detect license plates and introducing a spatial transformation network to automatically rectify and recognize license plates. Results show that this method is more accurate than other advanced methods.

JOURNAL OF ELECTRONIC IMAGING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Discriminative feature and dictionary learning with part-aware model for vehicle re-identification

Huibing Wang et al.

Summary: This paper proposes a part-aware model for vehicle re-identification, utilizing discriminative features in vehicle details to enhance recognition accuracy. By partitioning vehicles from horizontal and vertical directions to strengthen details and using external memory modules to emphasize consistency in each part, the model learns discriminating features effectively.

NEUROCOMPUTING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

AttributeNet: Attribute enhanced vehicle re-identification

Rodolfo Quispe et al.

Summary: Vehicle Re-Identification (V-ReID) is a critical task that associates the same vehicle across different camera viewpoints. This work proposes a new method to efficiently explore discriminative information from vehicle attributes and achieves state-of-the-art performance on three challenging datasets.

NEUROCOMPUTING (2021)

添加到收藏夹

Proceedings Paper

Two Stream Pose Guided Network for Vehicle Re-identification

Saifullah Tumrani et al.

Summary: Vehicle Re-Identification is a beneficial yet challenging task of finding images of the same vehicle with different views across a surveillance camera network. This paper proposes a deep learning technique that incorporates poses of vehicles generated by pose estimation network and visual information to tackle this task, showing competitiveness with recent state-of-the-art methods through experiments on benchmark datasets.

IPMV 2021: PROCEEDINGS OF 2021 3RD INTERNATIONAL CONFERENCE ON IMAGE PROCESSING AND MACHINE VISION (IPMV 2021) (2021)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

A Strong Baseline for Vehicle Re-Identification

Su Huynh et al.

Summary: This paper analyzes the technical challenges and proposes solutions for Vehicle Re-Identification, achieving significant improvement on the 5th AI City Challenge Track 2 dataset. The method outperforms previous works on the Veri benchmark.

2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021 (2021)

添加到收藏夹

Article Computer Science, Information Systems

Kernelized Multiview Subspace Analysis By Self-Weighted Learning

Huibing Wang et al.

Summary: In this paper, a general framework named KMSA is proposed for dimension reduction of multiview data, which can fully exploit information and differentiate between different views. With the co-regularized term and self-weighted learning, KMSA can learn appropriate weights for all views effectively.

IEEE TRANSACTIONS ON MULTIMEDIA (2021)

添加到收藏夹

Article Engineering, Civil

Vehicle Re-Identification Using Quadruple Directional Deep Learning Features

Jianqing Zhu et al.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)

添加到收藏夹

Review Computer Science, Artificial Intelligence

Multi-scale attention vehicle re-identification

Aihua Zheng et al.

NEURAL COMPUTING & APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Information Systems

Vehicle re-identification using multi-task deep learning network and spatio-temporal model

Jinjia Peng et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Partial attention and multi-attribute learning for vehicle re-identification

Saifullah Tumrani et al.

PATTERN RECOGNITION LETTERS (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Multi-Path Deep CNNs for Fine-Grained Car Recognition

Huibing Wang et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Attribute-Guided Feature Learning Network for Vehicle Reidentification

Huibing Wang et al.

IEEE MULTIMEDIA (2020)

添加到收藏夹

Article Computer Science, Information Systems

VRSDNet: vehicle re-identification with a shortly and densely connected convolutional neural network

Jianqing Zhu et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Adaptive deep metric embeddings for person re-identification under occlusions

Wanxiang Yang et al.

NEUROCOMPUTING (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Embedding Adversarial Learning for Vehicle Re-Identification

Yihang Lou et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

添加到收藏夹

Article Engineering, Electrical & Electronic

Chinese license plate image database building methodology for license plate recognition

Youting Zhao et al.

JOURNAL OF ELECTRONIC IMAGING (2019)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

Zheng Tang et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)

添加到收藏夹

Article Computer Science, Information Systems

PROVID: Progressive and Multimodal Vehicle Reidentification for Large-Scale Urban Surveillance

Xinchen Liu et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2018)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification

Yi Zhou et al.

2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2018)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Exploiting Multi-Grain Ranking Constraints for Precisely Searching Visually-similar Vehicles

Ke Yan et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-temporal Path Proposals

Yantao Shen et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.