{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T09:04:23Z","timestamp":1765357463845,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Distinguished Young Scholars Funding of Dalian","award":["No. 2022RJ01"],"award-info":[{"award-number":["No. 2022RJ01"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972067\/U21A20491"],"award-info":[{"award-number":["61972067\/U21A20491"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022ZD0210500"],"award-info":[{"award-number":["2022ZD0210500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3612147","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:26:54Z","timestamp":1698391614000},"page":"3138-3148","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Event-Enhanced Multi-Modal Spiking Neural Network for Dynamic Obstacle Avoidance"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3369-6772","authenticated-orcid":false,"given":"Yang","family":"Wang","sequence":"first","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9189-9506","authenticated-orcid":false,"given":"Bo","family":"Dong","sequence":"additional","affiliation":[{"name":"Princeton University, Princeton, NJ, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5402-7503","authenticated-orcid":false,"given":"Yuji","family":"Zhang","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7817-3724","authenticated-orcid":false,"given":"Yunduo","family":"Zhou","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3549-9684","authenticated-orcid":false,"given":"Haiyang","family":"Mei","sequence":"additional","affiliation":[{"name":"Dalian University of Technology &amp; National University of Singapore, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9402-8386","authenticated-orcid":false,"given":"Ziqi","family":"Wei","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences &amp; Dalian University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8046-722X","authenticated-orcid":false,"given":"Xin","family":"Yang","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abf2756"},{"key":"e_1_3_2_1_2_1","volume-title":"Exploration of reinforcement learning for event camera using car-like robots. arXiv preprint arXiv:2004.00801","author":"Arakawa Riku","year":"2020","unstructured":"Riku Arakawa and Shintaro Shiba. 2020. Exploration of reinforcement learning for event camera using car-like robots. arXiv preprint arXiv:2004.00801 (2020)."},{"key":"e_1_3_2_1_3_1","volume-title":"RSS 2017","author":"Blum Hermann","year":"2017","unstructured":"Hermann Blum, Alexander Dietm\u00fcller, Moritz Milde, J\u00f6rg Conradt, Giacomo Indiveri, and Yulia Sandamirskaya. 2017. A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor. Robotics Science and Systems, RSS 2017 (2017)."},{"key":"e_1_3_2_1_4_1","volume-title":"Error-backpropagation in temporally encoded networks of spiking neurons. Neurocomputing","author":"Bohte Sander M","year":"2002","unstructured":"Sander M Bohte, Joost N Kok, and Han La Poutre. 2002. Error-backpropagation in temporally encoded networks of spiking neurons. Neurocomputing (2002)."},{"key":"e_1_3_2_1_5_1","volume-title":"meta-dynamic neurons in spiking neural networks for spatio-temporal learning. arXiv preprint arXiv:2010.03140","author":"Cheng Xiang","year":"2020","unstructured":"Xiang Cheng, Tielin Zhang, Shuncheng Jia, and Bo Xu. 2020. meta-dynamic neurons in spiking neural networks for spatio-temporal learning. arXiv preprint arXiv:2010.03140 (2020)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abk3268"},{"key":"e_1_3_2_1_7_1","unstructured":"Jianchuan Ding Bo Dong Felix Heide Yufei Ding Yunduo Zhou Baocai Yin and Xin Yang. 2022. Biologically Inspired Dynamic Thresholds for Spiking Neural Networks. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2898117"},{"key":"e_1_3_2_1_9_1","unstructured":"C. Florensa D. Held M. Wulfmeier and P. Abbeel. 2017. Reverse Curriculum Generation for Reinforcement Learning. (2017)."},{"key":"e_1_3_2_1_10_1","unstructured":"Guillermo Gallego Tobi Delbr\u00fcck Garrick Orchard Chiara Bartolozzi Brian Taba Andrea Censi Stefan Leutenegger Andrew J Davison J\u00f6rg Conradt Kostas Daniilidis et al. 2020. Event-based vision: A survey. IEEE transactions on pattern analysis and machine intelligence (2020)."},{"key":"e_1_3_2_1_11_1","volume-title":"Time structure of the activity in neural network models. Physical review E","author":"Gerstner Wulfram","year":"1995","unstructured":"Wulfram Gerstner. 1995. Time structure of the activity in neural network models. Physical review E (1995)."},{"volume-title":"Spiking neuron models: Single neurons, populations, plasticity","author":"Gerstner Wulfram","key":"e_1_3_2_1_12_1","unstructured":"Wulfram Gerstner and Werner M Kistler. 2002. Spiking neuron models: Single neurons, populations, plasticity. Cambridge university press."},{"volume-title":"Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration","author":"Jia Shuncheng","key":"e_1_3_2_1_13_1","unstructured":"Shuncheng Jia, Ruichen Zuo, Tielin Zhang, Hongxing Liu, and Bo Xu. 2022. Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8917--8921."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20665"},{"key":"e_1_3_2_1_15_1","volume-title":"Complementary Multi-Modal Sensor Fusion for Resilient Robot Pose Estimation in Subterranean Environments. In IEEE International Conference on Unmanned Aircraft Systems","author":"Khattak S.","year":"2020","unstructured":"S. Khattak, H. D. Nguyen, F. Mascarich, T. Dang, and K. Alexis. 2020. Complementary Multi-Modal Sensor Fusion for Resilient Robot Pose Estimation in Subterranean Environments. In IEEE International Conference on Unmanned Aircraft Systems 2020."},{"key":"e_1_3_2_1_16_1","volume-title":"Jongkil Park, Suyoun Lee, Inho Kim, Jong-Keuk Park, and YeonJoo Jeong.","author":"Kim Taeyoon","year":"2021","unstructured":"Taeyoon Kim, Suman Hu, Jaewook Kim, Joon Young Kwak, Jongkil Park, Suyoun Lee, Inho Kim, Jong-Keuk Park, and YeonJoo Jeong. 2021. Spiking neural network (snn) with memristor synapses having non-linear weight update. Frontiers in computational neuroscience, Vol. 15 (2021), 646125."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747906"},{"key":"e_1_3_2_1_18_1","volume-title":"Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114","author":"Kingma Diederik P","year":"2013","unstructured":"Diederik P Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2004.1389727"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2007.914337"},{"key":"e_1_3_2_1_21_1","volume-title":"Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971","author":"Lillicrap Timothy P","year":"2015","unstructured":"Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra. 2015. Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971 (2015)."},{"key":"e_1_3_2_1_22_1","volume-title":"Event-Based Multimodal Spiking Neural Network with Attention Mechanism. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).8922--8926","author":"Liu Qianhui","year":"2022","unstructured":"Qianhui Liu, Dong Xing, Lang Feng, Huajin Tang, and Gang Pan. 2022. Event-Based Multimodal Spiking Neural Network with Attention Mechanism. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).8922--8926."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966127"},{"key":"e_1_3_2_1_24_1","series-title":"Series B. Biological Sciences","volume-title":"A computational theory of human stereo vision. Proceedings of the Royal Society of London","author":"Marr David","year":"1979","unstructured":"David Marr and Tomaso Poggio. 1979. A computational theory of human stereo vision. Proceedings of the Royal Society of London. Series B. Biological Sciences, Vol. 204, 1156 (1979), 301--328."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02121"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01212"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver Andrei A Rusu Joel Veness Marc G Bellemare Alex Graves Martin Riedmiller Andreas K Fidjeland Georg Ostrovski et al. 2015. Human-level control through deep reinforcement learning. nature Vol. 518 7540 (2015) 529--533.","DOI":"10.1038\/nature14236"},{"key":"e_1_3_2_1_28_1","unstructured":"Michael Montemerlo Sebastian Thrun Daphne Koller Ben Wegbreit et al. 2002. FastSLAM: A factored solution to the simultaneous localization and mapping problem. Aaai\/iaai Vol. 593598 (2002)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ECMR.2015.7324048"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2869644"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2018.2872014"},{"key":"e_1_3_2_1_32_1","volume-title":"Diet-snn: Direct input encoding with leakage and threshold optimization in deep spiking neural networks. arXiv preprint arXiv:2008.03658","author":"Rathi Nitin","year":"2020","unstructured":"Nitin Rathi and Kaushik Roy. 2020. Diet-snn: Direct input encoding with leakage and threshold optimization in deep spiking neural networks. arXiv preprint arXiv:2008.03658 (2020)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/DASC50938.2020.9256492"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9196877"},{"key":"e_1_3_2_1_35_1","volume-title":"Martin Egelhaaf, and Elisabetta Chicca.","author":"Schoepe Thorben","year":"2021","unstructured":"Thorben Schoepe, Ella Janotte, Moritz B Milde, Olivier JN Bertrand, Martin Egelhaaf, and Elisabetta Chicca. 2021. Finding the gap: neuromorphic motion vision in cluttered environments. arXiv preprint arXiv:2102.08417 (2021)."},{"key":"e_1_3_2_1_36_1","volume-title":"Learning to time-decode in spiking neural networks through the information bottleneck. arXiv preprint arXiv:2106.01177","author":"Skatchkovsky Nicolas","year":"2021","unstructured":"Nicolas Skatchkovsky, Osvaldo Simeone, and Hyeryung Jang. 2021. Learning to time-decode in spiking neural networks through the information bottleneck. arXiv preprint arXiv:2106.01177 (2021)."},{"key":"e_1_3_2_1_37_1","volume-title":"Supervised learning in multilayer spiking neural networks. Neural computation","author":"Sporea Ioana","year":"2013","unstructured":"Ioana Sporea and Andr\u00e9 Gr\u00fcning. 2013. Supervised learning in multilayer spiking neural networks. Neural computation, Vol. 25, 2 (2013), 473--509."},{"key":"e_1_3_2_1_38_1","volume-title":"Gesture similarity analysis on event data using a hybrid guided variational auto encoder. arXiv preprint arXiv:2104.00165","author":"Stewart Kenneth","year":"2021","unstructured":"Kenneth Stewart, Andreea Danielescu, Lazar Supic, Timothy Shea, and Emre Neftci. 2021. Gesture similarity analysis on event data using a hybrid guided variational auto encoder. arXiv preprint arXiv:2104.00165 (2021)."},{"key":"e_1_3_2_1_39_1","volume-title":"Rate, not selectivity, determines neuronal population coding accuracy in auditory cortex. PLoS biology","author":"Sun Wensheng","year":"2017","unstructured":"Wensheng Sun and Dennis L Barbour. 2017. Rate, not selectivity, determines neuronal population coding accuracy in auditory cortex. PLoS biology, Vol. 15, 11 (2017), e2002459."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"T. Takahashi I. Takeuchi T. Koto S. Tadokoro and I. Noda. 2000. RoboCup-Rescue Disaster Simulator Architecture. In Robot Soccer World Cup.","DOI":"10.1007\/3-540-45324-5_42"},{"key":"e_1_3_2_1_41_1","volume-title":"Computing with the leaky integrate-and-fire neuron: logarithmic computation and multiplication. Neural computation","author":"Tal Doron","year":"1997","unstructured":"Doron Tal and Eric L Schwartz. 1997. Computing with the leaky integrate-and-fire neuron: logarithmic computation and multiplication. Neural computation, Vol. 9, 2 (1997), 305--318."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-64556-4_5"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340948"},{"volume-title":"Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control. In Conference on Robot Learning.","author":"Tang Guangzhi","key":"e_1_3_2_1_44_1","unstructured":"Guangzhi Tang, Neelesh Kumar, Raymond Yoo, and Konstantinos P. Michmizos. 2020b. Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control. In Conference on Robot Learning."},{"key":"e_1_3_2_1_45_1","volume-title":"Tee Hiang Cheng, and Meng-Hiot Lim","author":"Wang Siqi","year":"2022","unstructured":"Siqi Wang, Tee Hiang Cheng, and Meng-Hiot Lim. 2022. LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2018.2849942"},{"key":"e_1_3_2_1_47_1","volume-title":"Spatio-temporal backpropagation for training high-performance spiking neural networks. Frontiers in neuroscience","author":"Wu Yujie","year":"2018","unstructured":"Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, and Luping Shi. 2018. Spatio-temporal backpropagation for training high-performance spiking neural networks. Frontiers in neuroscience, Vol. 12 (2018), 331."},{"key":"e_1_3_2_1_48_1","volume-title":"Attention spiking neural networks. arXiv preprint arXiv:2209.13929","author":"Yao Man","year":"2022","unstructured":"Man Yao, Guangshe Zhao, Hengyu Zhang, Yifan Hu, Lei Deng, Yonghong Tian, Bo Xu, and Guoqi Li. 2022b. Attention spiking neural networks. arXiv preprint arXiv:2209.13929 (2022)."},{"key":"e_1_3_2_1_49_1","volume-title":"GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks. In Advances in Neural Information Processing Systems.","author":"Yao Xingting","year":"2022","unstructured":"Xingting Yao, Fanrong Li, Zitao Mo, and Jian Cheng. 2022a. GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-016-0439-4"},{"key":"e_1_3_2_1_51_1","volume-title":"Multiscale Dynamic Coding improved Spiking Actor Network for Reinforcement Learning. AAAI","author":"Zhang Duzhen","year":"2022","unstructured":"Duzhen Zhang, Tielin Zhang, Shuncheng Jia, and Bo Xu. 2022b. Multiscale Dynamic Coding improved Spiking Actor Network for Reinforcement Learning. AAAI (2022)."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3588432.3591511"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00860"},{"key":"e_1_3_2_1_54_1","volume-title":"Decision-Making and Reasoning Mechanism for Human-Like Navigation. arXiv preprint arXiv:2207.11901","author":"Zhang Wenqi","year":"2022","unstructured":"Wenqi Zhang, Kai Zhao, Peng Li, Xiao Zhu, Yongliang Shen, Yanna Ma, Yingfeng Chen, and Weiming Lu. 2022c. A Closed-Loop Perception, Decision-Making and Reasoning Mechanism for Human-Like Navigation. arXiv preprint arXiv:2207.11901 (2022)."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636370"}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Ottawa ON Canada","acronym":"MM '23"},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612147","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3612147","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T23:55:33Z","timestamp":1755820533000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612147"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":55,"alternative-id":["10.1145\/3581783.3612147","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3612147","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}