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Paper list for event camera (spiking neural network) based tracking

  • SpikeMOT: Event-based Multi-Object Tracking with Sparse Motion Features, Song Wang, Zhu Wang, Can Li, Xiaojuan Qi, Hayden Kwok-Hay So [Paper]

  • [IJCV-2023] A Universal Event-Based Plug-In Module for Visual Object Tracking in Degraded Conditions[J]. Zhang J, Dong B, Fu Y, et al. International Journal of Computer Vision, 2023: 1-23. [Paper]

  • [arXiv-2023] Single-Model and Any-Modality for Video Object Tracking, Zongwei Wu, Jilai Zheng, Xiangxuan Ren, Florin-Alexandru Vasluianu, Chao Ma* Danda Pani Paudel, Luc Van Gool, Radu Timofte [Paper] [Code]

  • [IEEE TIP-2023] Distractor-aware Event-based Tracking, Yingkai Fu, Meng Li, Wenxi Liu, Yuanchen Wang, Jiqing Zhang, Baocai Yin, Xiaopeng Wei, Xin Yang [Paper] [IEEE]

  • [ICCV-2023] "Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers." Zhiyu Zhu, Junhui Hou, Dapeng Oliver Wu. ICCV 2023, [Paper] [Code]

  • [CVPR-2023] Frame-Event Alignment and Fusion Network for High Frame Rate Tracking Jiqing Zhang · Yuanchen Wang · Wenxi Liu · Meng Li · Jinpeng Bai · Baocai Yin · Xin Yang [Paper] [Code]

  • [CVPR-2023] Visual Prompt Multi-Modal Tracking, Jiawen Zhu, Simiao Lai, Xin Chen, Dong Wang, Huchuan Lu, [Paper] [Code]

  • Spike-based Motion Estimation for Object Tracking through Bio-inspired Unsupervised Learning, Yajing Zheng, Zhaofei Yu, Song Wang, Tiejun Huang, IEEE TRANSACTIONS ON IMAGE PROCESSING (TIP), 2022, [Paper]

  • Event-based Visual Tracking in Dynamic Environments, Irene Perez-Salesa, Rodrigo Aldana-Lopez, and Carlos Sag ´u¨es, arXiv 2212.07754, [Paper]

  • Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric, Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang, Lin Zhu, Jianlin Zhang, Yaowei Wang, Yonghong Tian [Paper] [DemoVideo] [Github]

  • Data-driven Feature Tracking for Event Cameras, Nico Messikommer* Carter Fang∗ Mathias Gehrig Davide Scaramuzza [Paper] [DemoVideo]

  • [NIPS 2022] Learning Graph-embedded Key-event Back-tracing for Object Tracking in Event Clouds, Zhiyu ZHU, Junhui HOU, Xianqiang LYU [Paper] [Code]

  • Prompting for Multi-Modal Tracking, Jinyu Yang, Zhe Li, Feng Zheng, Aleš Leonardis, Jingkuan Song, [Paper]

  • STNet: Spiking Transformers for Event-based Single Object Tracking, Jiqing Zhang, Bo Dong, Haiwei Zhang, Jianchuan Ding, Felix Heide, Baocai Yin, Xin Yang [Paper] [Project] [Code]

  • VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows. Wang, Xiao, et al. arXiv preprint arXiv:2108.05015 (2021).

  • Luo, Yihao, et al. "Conversion of Siamese networks to spiking neural networks for energy-efficient object tracking." Neural Computing and Applications (2022): 1-16. [Paper]

  • Zhang J, Yang X, Fu Y, et al. Object Tracking by Jointly Exploiting Frame and Event Domain [C]//Proceedings of the IEEE/CVF International Conference on Computer Vision. 2021: 13043-13052.

  • Real-Time Event-Based Tracking and Detection for Maritime Environments, Stephanie Aelmore, Richard C. Ordonez, Shibin Parameswaran, and Justin Mauger, IEEE AIPR 2021 (Oral) [Paper]

  • Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking，CGI 2021, Jiqing Zhang， Kai Zhao， Bo Dong， Yingkai Fu， Yuxin Wang， Xin Yang， Baocai Yin [Paper]

  • Deng, Lei, et al. "Fast object tracking on a many-core neural network chip." Frontiers in Neuroscience 12 (2018): 841. [Paper]

  • Jiang, Rui, et al. "Object tracking on event cameras with offline–online learning." CAAI Transactions on Intelligence Technology (2020) [Paper]

  • Retinal Slip Estimation and Object Tracking with an Active Event Camera [AICAS-2020]

  • Zhang, Y. (2019). Real‑time object tracking for event cameras. Master's thesis, Nanyang Technological University, Singapore. [Thesis]

  • Yang, Zheyu, et al. "DashNet: A hybrid artificial and spiking neural network for high-speed object tracking." arXiv preprint arXiv:1909.12942 (2019). [Paper]

  • End-to-end Learning of Object Motion Estimation from Retinal Events for Event-based Object Tracking, aaai-2020 [Paper]

  • HASTE: multi-Hypothesis Asynchronous Speeded-up Tracking of Events, bmvc2020, [Paper]

  • High-speed event camera tracking, bmvc2020, [Paper]

  • A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-time Systems, [Paper] [Code] [Demo]

  • Long-term object tracking with a moving event camera. Ramesh, Bharath, et al. Bmvc. 2018. [Paper]

  • e-TLD: Event-based Framework for Dynamic Object Tracking, [Paper] [Dataset]

  • Spiking neural network-based target tracking control for autonomous mobile robots. Cao, Zhiqiang, et al. Neural Computing and Applications 26.8 (2015): 1839-1847. [Paper]

  • Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking, Chen, Haosheng, et al. Proceedings of the 27th ACM International Conference on Multimedia. 2019. [Paper]

  • High-Speed Object Tracking with Dynamic Vision Sensor. Wu, J., Zhang, K., Zhang, Y., Xie, X., & Shi, G. (2018, October).
    In China High Resolution Earth Observation Conference (pp. 164-174). Springer, Singapore. [Paper]

  • High-speed object tracking with its application in golf playing. Lyu, C., Liu, Y., Jiang, X., Li, P., & Chen, H. (2017).
    International Journal of Social Robotics, 9(3), 449-461. [Paper]

  • A Spiking Neural Network Architecture for Object Tracking. Luo, Yihao, et al.
    International Conference on Image and Graphics. Springer, Cham, 2019. [Paper]

  • SiamSNN: Spike-based Siamese Network for Energy-Efficient and Real-time Object Tracking, Yihao Luo, Min Xu, Caihong Yuan, Xiang Cao, Liangqi Zhang, Yan Xu, Tianjiang Wang and Qi Feng [Paper]

  • Event-guided structured output tracking of fast-moving objects using a CeleX sensor. Huang, Jing, et al.
    IEEE Transactions on Circuits and Systems for Video Technology 28.9 (2018): 2413-2417. [Paper]

  • EKLT: Asynchronous photometric feature tracking using events and frames." Gehrig, Daniel, et al.
    International Journal of Computer Vision 128.3 (2020): 601-618. [Paper] [Code]
    [Video]

  • Spatiotemporal Multiple Persons Tracking Using Dynamic Vision Sensor, Piątkowska, Ewa, et al. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. IEEE, 2012. [Paper]

  • Event-Driven Stereo Visual Tracking Algorithm to Solve Object Occlusion, IEEE TNNLS [Paper]

  • Ni, Zhenjiang, et al. "Asynchronous event‐based high speed vision for microparticle tracking." Journal of microscopy 245.3 (2012): 236-244. [Paper]

  • SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking, CVPR-2024, Xiaojun Hou, Jiazheng Xing, Yijie Qian, Yaowei Guo, Shuo Xin, Junhao Chen, Kai Tang, Mengmeng Wang, Zhengkai Jiang, Liang Liu, Yong Liu [Paper] [Code]

  • [SeqTrackv2] Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking, Xin Chen, Ben Kang, Jiawen Zhu, Dong Wang, Houwen Peng, Huchuan Lu [SeqTrackv2]

  • [arXiv:2405.05004] TENet: Targetness Entanglement Incorporating with Multi-Scale Pooling and Mutually-Guided Fusion for RGB-E Object Tracking, Pengcheng Shao, Tianyang Xu, Zhangyong Tang, Linze Li, Xiao-Jun Wu, Josef Kittler [Paper] [Code]

  • [arXiv:2405.17773] Towards a Generalist and Blind RGB-X Tracker, Yuedong Tan, Zongwei Wu, Yuqian Fu, Zhuyun Zhou, Guolei Sun, Chao Ma, Danda Pani Paudel, Luc Van Gool, Radu Timofte [Paper]

  • [arXiv:2405.17903] Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion, Hongze Sun, Rui Liu, Wuque Cai, Jun Wang, Yue Wang, Huajin Tang, Yan Cui, Dezhong Yao, Daqing Guo [Paper]