Browse State-of-the-Art › Multimodal Association
Multimodal Association
3 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
Multimodal association refers to the process of associating multiple modalities or types of data in time series analysis. In time series analysis, multiple modalities or types of data can be collected, such as sensor data, images, audio, and text. Multimodal association aims to integrate these different types of data to improve the understanding and prediction of the time series.
For example, in a smart home application, sensor data from temperature, humidity, and motion sensors can be combined with images from cameras to monitor the activities of residents. By analyzing the multimodal data together, the system can detect anomalies or patterns that may not be visible in individual modalities alone.
Multimodal association can be achieved using various techniques, including deep learning models, statistical models, and graph-based models. These models can be trained on the multimodal data to learn the associations and dependencies between the different types of data.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
3 shown of 3 papers with code (7 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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20 Sep 2022 1 repository listedViTag associates a sequence of vision tracker generated bounding boxes with Inertial Measurement Unit (IMU) data and Wi-Fi Fine Time Measurements (FTM) from smartphones.
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25 Jul 2022 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedWhile vision-and-language models perform well on tasks such as visual question answering, they struggle when it comes to basic human commonsense reasoning skills.
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18 Jul 2022 1 repository listedIn this paper, we present Vi-Fi, a multi-modal system that leverages a user’s smartphone WiFi Fine Timing Measurements (FTM) and inertial measurement unit (IMU) sensor data to associate the user detected on a camera…
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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