These advancements have enabled researchers to create feature description models that surpass traditional two-dimensional approaches. This progress has been facilitated by the development of additional sensors, driven by advancements in areas such as 3D gaming and self-driving vehicles. With the widespread use of 3D sensor data and 3D modeling, the analysis and representation of the world in three dimensions have become commonplace. We provide critical insights into the progress made in developing higher-dimensional qualities through the application of DL, and also discuss the advantages and strategies employed in DL. Particularly in the realm of more complex, three-dimensional (3D) data such as video and 3D models, CV and multimedia retrieval remain at the forefront of technological advancements. However, it is important to note that older CV techniques, developed prior to the emergence of DL, still hold value and relevance. Deep learning (DL) has revolutionized advanced digital picture processing, enabling significant advancements in computer vision (CV).
