Enhancing Part Features via Contrastive Attention Module for Vehicle Re-identification-Reference-Cited by-同舟云学术

Enhancing Part Features via Contrastive Attention Module for Vehicle Re-identification

Published:2022-10-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Image Processing (ICIP)
language:
Short-container-title:

Author:

Li Manyu¹,Wei Mengwan²,He Xin³,Shen Fei⁴

Affiliation:

1. Nanchang University,Nanchang,China

2. Seismological Bureau of Jiangsu Province,Nanjing,China

3. HUAWEI Technology Co., Ltd,Hangzhou,China

4. Nanjing University of Science and Technology,Nanjing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9897158/9897159/09897943.pdf?arnumber=9897943

Reference26 articles.

1. A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification

2. Exploring spatial significance via hybrid pyramidal graph network for vehicle re-identification;shen;IEEE Transactions on Intelligent Transportation Systems,2021

3. Vehicle Re-Identification With Viewpoint-Aware Metric Learning

4. Learning attention-guided pyramidal features for few-shot fine-grained recognition

5. PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-09-06

2. LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. MIPANet: optimizing RGB-D semantic segmentation through multi-modal interaction and pooling attention;Frontiers in Physics;2024-05-31

4. RAFBSD: An Efficient Detector for Accurate Identification of Defects in Photovoltaic Cells;IEEE Access;2024

5. AMANet: Advancing SAR Ship Detection With Adaptive Multi-Hierarchical Attention Network;IEEE Access;2024