Three papers by 3D geospatial vision group has been published in the top-tier journals - ISPRS and IEEE Trans ITS
17 Nov 2022
Recently, team member -Shaocheng’s paper titled “Joint Learning of Frequency and Spatial Domains for Dense Image Prediction” has been published in the top-tier journal in the field of Geomatics - ISPRS Journal of Photogrammetry and Remote Sensing. In this work, we fully explore frequency domain learning and propose a joint learning paradigm of frequency and spatial domains. This paradigm can take full advantage of the combined preponderances of frequency learning and spatial learning; specifically, frequency and spatial domain learning can effectively capture intrinsic global and local information, respectively. To achieve this, an innovative but effective linear learning block is proposed to conduct the learning process directly in the frequency domain. Together with the prevailing spatial learning operation, i.e., convolution, a powerful and scalable joint learning framework is established.
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