Blog

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  Enabling Accurate Positioning in NLOS Scenarios by Hybrid Machine Learning with Denoising and Inpainting

  The growing interests on accurate positioning has been developed from thriving applications/services including the cellular network operation. The classical positioning methods mostly rely on information extracted from channel information, e.g., time of arrival, angle of arrival (or departure).

  On January 25, 2023

  Longhai Zhao Qi Xiong
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  DH-LC: Hierarchical Matching and Hybrid Bundle Adjustment Towards Accurate and Robust Loop Closure

  Visual simultaneous localization and mapping (SLAM) inevitably produces the accumulated drift in mapping and localization due to camera calibration errors, feature matching errors, etc. It is challenging to achieve drift-free localization and obtain an accurate global map.

  On January 18, 2023

  Xiongfeng Peng with 2 authors
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  FlowFormer: A Transformer Architecture for Optical Flow

  Optical flow targets at estimating per-pixel correspondences between a source image and a target image, in the form of a 2D displacement field.

  On January 12, 2023

  Chao Zhang Qiang Wang