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Paper Detail

Paper IDIMT-CIF-1.8
Paper Title TWO HEADED DRAGONS: MULTIMODAL FUSION AND CROSS MODAL TRANSACTIONS
Authors Rupak Bose, Shivam Pande, Biplab Banerjee, Indian Institute of Technology Bombay, India
SessionIMT-CIF-1: Computational Imaging 1
LocationArea J
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Computational Image Formation: Multi-image & sensor fusion
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract As the field of remote sensing is evolving, we witness the accumulation of information from several modalities, such as multispectral (MS), hyperspectral (HSI), LiDAR etc. Each of these modalities possess its own distinct characteristics and when combined synergistically, perform very well in the recognition and classification tasks. However, fusing multiple modalities in remote sensing is cumbersome due to highly disparate domains. Furthermore, the existing methods do not facilitate cross-modal interactions. To this end, we propose a novel transformer based fusion method for HSI and LiDAR modalities. The model is composed of stacked auto encoders that harness the cross key-value pairs for HSI and LiDAR, thus establishing a communication between the two modalities, while simultaneously using the CNNs to extract the spectral and spatial information from HSI and LiDAR. We test our model on Houston (Data Fusion Contest – 2013) and MUUFL Gulfport datasets and achieve competitive results.