A Comparative Analysis of Traditional Deep Learning Framework for 3D Object Pose Estimation
Davesh Singh Som, Pawan Kumar Goel, Deepak Singh Rana, Anurag Aeron, Raman Kumar · 2024
3-d object pose estimation is an essential mission for expertise three-D scenes, and it has won sizeable attention in current years, its various applications in robotics, augmented reality, and autonomous riding. Deep trendy has emerged as a powerful approach for 3D item pose estimation ultra-modern its capability to automatically research features from raw records and capture complicated spatial relationships. On this look, we behavior a comparative evaluation of cutting-edge conventional deep contemporary frameworks for 3-d item pose estimation. We assessment the conventional strategies used for three-D item pose estimation and their obstacles. Then, we discuss the idea present day deep present day and how it has been implemented to this venture. We compare the performance of different deep getting to know modern frameworks, together with Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative adverse Networks (GANs), on benchmark datasets for 3-d item pose estimation.