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Cross-modality fusing complementary information from different modalities effectively improves object detection performance, making it more useful and robust for a wider range of applications.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2014
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Faster R-CNN: towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross B. Girshick, and Jian Sun · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Multispectral deep neural networks for pedestrian detection
Jingjing Liu, Shaoting Zhang, Shu Wang, and Dimitris N. Metaxas · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Kumar Divvala, Ross B. Girshick, and Ali Farhadi · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Cascade R-CNN: delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Fusion of multispectral data through illumination-aware deep neural networks for pedestrian detection
Dayan Guan, Yanpeng Cao, Jiangxin Yang, Yanlong Cao, and Michael Ying Yang · 2019
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Illumination-aware faster R-CNN for robust multispectral pedestrian detection
Chengyang Li, Dan Song, Ruofeng Tong, and Min Tang · 2019
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GFD-SSD: gated fusion double SSD for multispectral pedestrian detection
Yang Zheng, Izzat H. Izzat, and Shahrzad Ziaee · 2019
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Multispectral fusion for object detection with cyclic fuse-and-refine blocks
Heng Zhang, Élisa Fromont, Sébastien Lefèvre, and Bruno Avignon · 2020
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Didfuse: Deep image decomposition for infrared and visible image fusion
Zixiang Zhao, Shuang Xu, Chunxia Zhang, Junmin Liu, Jiangshe Zhang, and Pengfei Li · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Cross-modality fusion transformer for multispectral object detection
Qingyun Fang, Dapeng Han, and Zhaokui Wang · 2021
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LLVIP: A visible-infrared paired dataset for low-light vision
Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, and Wenli Zhou · 2021
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Sdnet: A versatile squeeze-and-decomposition network for real-time image fusion
Hao Zhang and Jiayi Ma · 2021
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Guided attentive feature fusion for multispectral pedestrian detection
Heng Zhang, Élisa Fromont, Sébastien Lefèvre, and Bruno Avignon · 2021
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Multimodal object detection via probabilistic ensembling
Yi-Ting Chen, Jinghao Shi, Zelin Ye, Christoph Mertz, Deva Ramanan, and Shu Kong · 2022
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ultralytics/yolov5: v6. 2-yolov5 classification models, apple m1, reproducibility, clearml and deci. ai integrations
Glenn Jocher, Ayush Chaurasia, Alex Stoken, Jirka Borovec, Yonghye Kwon, Kalen Michael, Jiacong Fang, Colin Wong, Zeng Yifu, Diego Montes, et al · 2022
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Explicit attention-enhanced fusion for rgb-thermal perception tasks
Mingjian Liang, Junjie Hu, Chenyu Bao, Hua Feng, Fuqin Deng, and Tin Lun Lam · 2023
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Divfusion: Darkness-free infrared and visible image fusion
Linfeng Tang, Xinyu Xiang, Hao Zhang, Meiqi Gong, and Jiayi Ma · 2023
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YOLO-MS: multispectral object detection via feature interaction and self-attention guided fusion
Yumin Xie, Langwen Zhang, Xiaoyuan Yu, and Wei Xie · 2023
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Dense distinct query for end-to-end object detection
Shilong Zhang, Xinjiang Wang, Jiaqi Wang, Jiangmiao Pang, Chengqi Lyu, Wenwei Zhang, Ping Luo, and Kai Chen · 2023
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Cddfuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion
Zixiang Zhao, Haowen Bai, Jiangshe Zhang, Yulun Zhang, Shuang Xu, Zudi Lin, Radu Timofte, and Luc Van Gool · 2023
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Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection
Jinyuan Liu, Xin Fan, Zhanbo Huang, Guanyao Wu, Risheng Liu, Wei Zhong, and Zhongxuan Luo · 2022
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Detfusion: A detection-driven infrared and visible image fusion network
Yiming Sun, Bing Cao, Pengfei Zhu, and Qinghua Hu · 2022
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Superfusion: A versatile image registration and fusion network with semantic awareness
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Improving rgb-infrared object detection by reducing cross-modality redundancy
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Isnet: Shape matters for infrared small target detection
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Multimodal object detection by channel switching and spatial attention
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