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This paper proposes MambaST, a plug-and-play cross-spectral spatial-temporal fusion pipeline for efficient pedestrian detection.
“Learning spatiotemporal features with 3d convolutional networks”
Du Tran et al · 2015
Earlier work this paper cites.
“Multispectral pedestrian detection: Benchmark dataset and baseline”
Soonmin Hwang et al · 2015
Earlier work this paper cites.
“Multiview random forest of local experts combining rgb and lidar data for pedestrian detection”
Alejandro González et al · 2015
Earlier work this paper cites.
“Multispectral deep neural networks for pedestrian detection”
Jingjing Liu, Shaoting Zhang, Shu Wang and Dimitris Metaxas · 2016
Earlier work this paper cites.
“You only look once: Unified, real-time object detection”
Joseph Redmon, Santosh Divvala, Ross Girshick and Ali Farhadi · 2016
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“Quo vadis, action recognition? a new model and the kinetics dataset”
Joao Carreira and Andrew Zisserman · 2017
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“Attention is all you need”
Ashish Vaswani et al · 2017
Earlier work this paper cites.
“Multispectral pedestrian detection via simultaneous detection and segmentation”
Chengyang Li, Dan Song, Ruofeng Tong and Min Tang · 2018
Earlier work this paper cites.
“Pyramid attention network for semantic segmentation”
Hanchao Li, Pengfei Xiong, Jie An and Lingxue Wang · 2018
Earlier work this paper cites.
“Cross-modality interactive attention network for multispectral pedestrian detection”
Lu Zhang et al · 2019
Earlier work this paper cites.
“Video classification with channel-separated convolutional networks”
Du Tran, Heng Wang, Lorenzo Torresani and Matt Feiszli · 2019
Earlier work this paper cites.
“Slowfast networks for video recognition”
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik and Kaiming He · 2019
Earlier work this paper cites.
“Rgb and lidar fusion based 3d semantic segmentation for autonomous driving”
Khaled El et al · 2019
Earlier work this paper cites.
“Motion and depth augmented semantic segmentation for autonomous navigation”
Hazem Rashed, Ahmad El, Senthil Yogamani and Mohamed ElHelw · 2019
Earlier work this paper cites.
“Weakly aligned cross-modal learning for multispectral pedestrian detection”
Lu Zhang et al · 2019
Earlier work this paper cites.
“Lrpd: Long range 3d pedestrian detection leveraging specific strengths of lidar and rgb”
Michael Fürst, Oliver Wasenmüller and Didier Stricker · 2020
Earlier work this paper cites.
“Rgb-depth fusion framework for object detection in autonomous vehicles”
Fahimeh Farahnakian and Jukka Heikkonen · 2020
Cited alongside, same era.
“Attention based multi-layer fusion of multispectral images for pedestrian detection”
Yongtao Zhang, Zhishuai Yin, Linzhen Nie and Song Huang · 2020
Cited alongside, same era.
“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”
Alexey Dosovitskiy et al · 2020
Cited alongside, same era.
“Multispectral fusion for object detection with cyclic fuse-and-refine blocks”
Heng Zhang, Elisa Fromont, Sébastien Lefevre and Bruno Avignon · 2020
Cited alongside, same era.
“Learning to detect pedestrian flow in traffic intersections from synthetic data”
Abhijit Baul et al · 2021
Cited alongside, same era.
“Guided attentive feature fusion for multispectral pedestrian detection”
“A Lightweight RGB-T Fusion Network for Practical Semantic Segmentation”
Haoyuan Zhang, Zifeng Li, Zhenyu Wu and Danwei Wang · 2023
Later among the works it cites.
“Mamba: Linear-time sequence modeling with selective state spaces”
Albert Gu and Tri Dao · 2023
Later among the works it cites.
“Stabilizing multispectral pedestrian detection with evidential hybrid fusion”
Qing Li et al · 2023
Later among the works it cites.
Yinghui Xing et al · 2023
Later among the works it cites.
“Multi-modal feature pyramid transformer for rgb-infrared object detection”
Yaohui Zhu, Xiaoyu Sun, Miao Wang and Hua Huang · 2023
Later among the works it cites.
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Heng Zhang, Elisa Fromont, Sébastien Lefèvre and Bruno Avignon · 2021
Cited alongside, same era.
“Multimodal object detection via bayesian fusion”
Yi-Ting Chen et al · 2021
Cited alongside, same era.
“TAda! Temporally-Adaptive Convolutions for Video Understanding”
Ziyuan Huang et al · 2021
Cited alongside, same era.
“Tam: Temporal adaptive module for video recognition”
Zhaoyang Liu et al · 2021
Cited alongside, same era.
“Cross-modality fusion transformer for multispectral object detection”
Fang Qingyun, Han Dapeng and Wang Zhaokui · 2021
Cited alongside, same era.
“Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention”
Dongfang Yang et al · 2022
Cited alongside, same era.
“Temporally efficient vision transformer for video instance segmentation”
Shusheng Yang et al · 2022
Cited alongside, same era.
“Towards large-scale small object detection: Survey and benchmarks”
Gong Cheng et al · 2023
Later among the works it cites.
“Vision mamba: Efficient visual representation learning with bidirectional state space model”
Lianghui Zhu et al · 2024
Closest in time.
Hanwei Zhang et al · 2024
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“A Survey on Vision Mamba: Models, Applications and Challenges”
Rui Xu et al · 2024
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“Vmamba: Visual state space model”
Yue Liu et al · 2024
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“Fusion-Mamba for Cross-modality Object Detection”
Wenhao Dong et al · 2024
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Haoyuan Li et al · 2024
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“Fusionmamba: Efficient image fusion with state space model”
Siran Peng et al · 2024
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“Videomamba: State space model for efficient video understanding”
Kunchang Li et al · 2024
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“INSANet: INtra-INter spectral attention network for effective feature fusion of multispectral pedestrian detection”
Sangin Lee et al · 2024
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