Siddiqui Muhammad Yasir1, Amin Muhammad Sadiq2, Hyunsik Ahn3,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5777-5791, 2022, DOI:10.32604/cmc.2022.025909
Abstract 3D object recognition is a challenging task for intelligent and robot systems in industrial and home indoor environments. It is critical for such systems to recognize and segment the 3D object instances that they encounter on a frequent basis. The computer vision, graphics, and machine learning fields have all given it a lot of attention. Traditionally, 3D segmentation was done with hand-crafted features and designed approaches that didn’t achieve acceptable performance and couldn’t be generalized to large-scale data. Deep learning approaches have lately become the preferred method for 3D segmentation challenges by their great success in 2D computer vision. However,… More >
Login
Register
