Max Robotics — Global Service Robot Directory + US Certification

About

Moein Shakeri’s research lies at the intersection of computer vision, robotics, and computational imaging, with a focus on enabling real-time scene understanding for autonomous systems. His major contributions span shadow detection, high dynamic range (HDR) reconstruction, and polarimetric dense mapping, each addressing critical bottlenecks in visual perception. Shakeri’s most cited work, “Fast Shadow Detection from a Single Image Using a Patched Convolutional Neural Network” (2018, 53 citations), introduced a deep learning method that dramatically reduces time complexity, making shadow detection viable for robotic applications. He further advanced polarization-based imaging with “HDR Reconstruction Based on the Polarization Camera” (2020, 37 citations), leveraging on-chip micro-polarizer technology to capture synchronized multi-orientation data. In “Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior” (2021, 16 citations), Shakeri combined polarization cues with relative depth priors to improve surface normal estimation and dense reconstruction. His work on online mutual adaptation of depth prediction and visual SLAM (2021) addresses a key challenge in practical SLAM systems. With over 120 total citations, Shakeri’s research demonstrates a consistent drive to make advanced vision techniques computationally efficient and deployable in real-world robotics.