VOMTC: Vision Objects for Millimeter and Terahertz Communications
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Abstract (arXiv)
Recent advances in sensing and computer vision (CV) technologies have opened the door for the application of deep learning (DL)-based CV technologies in the realm of 6G wireless communications. For the successful application of this emerging technology, it is crucial to have a qualified vision dataset tailored for wireless applications (e.g., RGB images containing wireless devices such as laptops and cell phones). An aim of this paper is to propose a large-scale vision dataset referred to as Vision Objects for Millimeter and Terahertz Communications (VOMTC). The VOMTC dataset consists of 20,232 pairs of RGB and depth images obtained from a camera attached to the base station (BS), with each pair labeled with three representative object categories (person, cell phone, and laptop) and bounding boxes of the objects. Through experimental studies of the VOMTC datasets, we show that the beamforming technique exploiting the VOMTC-trained object detector outperforms conventional beamforming techniques.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 26 of its 58 references that are in the map. First posted on arXiv 14 Sep 2024.
Builds on
26 of 58 references.
References · 26
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14 more
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3 papers.