跨模态行人重识别
HPILN: A feature learning framework for cross modality person re-identification
zero-padding:《RGB-Infrared Cross-Modality Person Re-Identifification》
cmGAN ：《Cross-modality person re-identification with generative adversarial training》
BDTR：《Visible thermal person re-identification via dual-constrained top-ranking》
eBDTR：《Bi-directional center-constrained top ranking for visible thermal person re-identification》
HSME：《HSME: hypersphere manifold embedding for visible thermal person re-identification》
D2RL：《Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identifification》
对于近红外的跨模态的行人重识别问题，其根本目的是解决两种模态之间的gap，大致解决思路为以下两种：
使用参数共享的卷积网络，学习到两种模态数据之间的共享特征
使用GAN网络，通过训练生成器和判别器去学习模态之间的关联
2017-ICCV-RGB-Infrared Cross-Modality Person Re-Identification
2018-AAAI-Hierarchical Discriminative Learning for Visible Thermal Person Re-Identification
2018-IJCAI-Cross-Modality Person Re-Identification with Generative Adversarial Training
2018-IJCAI-Visible thermal person re-identification via dual-constrained top-ranking
2019-CVPR-Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification
2019-AAAI-HSME: Hypersphere Manifold Embedding for Visible Thermal Person Re-Identification
2019-IEEE Access-Person Re-Identification Between Visible and Thermal Camera Images Based on Deep Residual CNN Using Single Input
2019-ArXiv-Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person Re-Identification
2019-ICCV-RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
2019-IET IP-HPILN: A feature learning framework for cross-modality person re-identification
2019-ArXiv-Hetero-Center Loss for Cross-Modality Person Re-Identification
2019-ArXiv-Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation
多光谱行人检测
1] Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks. (ESANN, 2016)
[2] Multispectral Deep Neural Networks for Pedestrian Detection. (BMVC, 2016)
[3] Fully Convolutional Region Proposal Networks for Multispectral Person Detection. (CVPR, 2017)
[4] Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. (NIPS, 2015)
[5] Multispectral pedestrian detection: Benchmark dataset and baseline. (CVPR, 2015)
引用自：
https://blog.csdn.net/wjbwjbwjbwjb/article/details/100693828
https://blog.csdn.net/qq_34374211/article/details/103819059
https://blog.csdn.net/ylin01234/article/details/81106203
