{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:35:25Z","timestamp":1761176125002,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Multi-modal trackers have drawn widespread attention for robust tracking in challenging scenarios. However, existing multi-modal trackers often rely solely on spatial matching between the initial target template and the search regions, or incorporate only single-frame historical information, failing to fully exploit temporal correlations in tracking sequences. Additionally, most trackers that introduce temporal modeling require either retraining the entire network or designing specialized modules for temporal feature extraction, which incurs additional computational costs. To alleviate these limitations, inspired by human visual memory, we propose MPTrack, a novel tracker that directly reuses pre-extracted historical target features as memory prompts, establishing temporal dependencies without redundant feature extraction or specially designed temporal extraction networks. Our proposed Memory Prompt Fusion module effectively combines initial target templates with multiple historical memory cues to generate enhanced templates, enabling the perception of long-term appearance dynamics while mitigating potential interference from individual memory. Simultaneously, to avoid the computational cost of full-model training, we design a lightweight memory adapter that allows the frozen backbone network to efficiently adapt to the memory-enhanced template. Extensive experiments demonstrate that our method effectively incorporates temporal information and achieves promising results across different multi-modal tracking scenarios, including RGB+Thermal, RGB+Event, and RGB+Depth tracking tasks.<\/jats:p>","DOI":"10.3233\/faia250829","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:43:24Z","timestamp":1761126204000},"source":"Crossref","is-referenced-by-count":0,"title":["Memory Prompt for Multi-Modal Visual Object Tracking"],"prefix":"10.3233","author":[{"given":"Xueqi","family":"Li","sequence":"first","affiliation":[{"name":"Academy of Military Science"}]},{"given":"Yongjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Innovation Institute of Defense Technology"}]},{"given":"Jianqiang","family":"Xia","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"}]},{"given":"Fang","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Computer, National University of Defense Technology"}]},{"given":"Yuanyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Academy of Military Science"}]},{"given":"Yushe","family":"Cao","sequence":"additional","affiliation":[{"name":"School of computing, Tsinghua University"}]},{"given":"Junze","family":"Zhang","sequence":"additional","affiliation":[{"name":"Academy of Military Science"}]},{"given":"Dianxi","family":"Shi","sequence":"additional","affiliation":[{"name":"Academy of Military Science"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250829","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:43:24Z","timestamp":1761126204000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250829"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250829","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}